Distributed data set storage and retrieval

ABSTRACT

An apparatus includes a processor component caused to: retrieve metadata of organization of data within a data set, and map data of organization of data blocks within a data file; receive indications of which node devices are available to perform a processing task with a data set portion; and in response to the data set including partitioned data, compare the quantities of available node devices and of the node devices last involved in storing the data set. In response to a match, for each map data map entry: retrieve a hashed identifier for a data sub-block, and a size for each of the data sub-blocks within the corresponding data block; divide the hashed identifier by the quantity of available node devices; compare the modulo value to a designation assigned to each of the available node devices; and provide a pointer to the available node device assigned the matching designation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation under 35 U.S.C. § 120 of U.S.application Ser. No. 15/220,182 filed Jul. 26, 2016, which is acontinuation under 35 U.S.C. § 120 of U.S. application Ser. No.15/220,034 also filed Jul. 26, 2016 (and issued Apr. 11, 2017 as U.S.Pat. No. 9,619,148), which claims the benefit of priority under 35U.S.C. § 119(e) to U.S. Provisional Application Ser. No. 62/197,514filed Jul. 27, 2015, and U.S. Provisional Application Ser. No.62/197,519 also filed Jul. 27, 2015. The disclosures of U.S. applicationSer. No. 15/220,182, U.S. application Ser. No. 15/220,034, U.S.Provisional Application Ser. No. 62/197,514, and U.S. ProvisionalApplication Ser. No. 62/197,519 are hereby incorporated herein byreference in their respective entireties for all purposes.

TECHNICAL FIELD

Various embodiments described herein are generally directed tointer-device coordination and data set organization to improvedistributed storage and retrieval of a data set processed by multiplenode devices.

BACKGROUND

The performance of analyses of large data sets (e.g., what is commonlyreferred to as “big data”) is becoming increasingly commonplace in suchareas as simulations, process monitoring, decision making, behavioralmodeling and making predictions. Such analysis are often performed bygrids of varying quantities of available node devices, while the datasets are often stored within a separate set of storage devices. Thisbegets the challenge of efficiently exchanging such large data setsbetween storage devices and varying ones of the node devices among agrid of node devices.

SUMMARY

This summary is not intended to identify only key or essential featuresof the described subject matter, nor is it intended to be used inisolation to determine the scope of the described subject matter. Thesubject matter should be understood by reference to appropriate portionsof the entire specification of this patent, any or all drawings, andeach claim.

An apparatus may include a processor component and a storage to storeinstructions that, when executed by the processor component, may causethe processor component to retrieve, from one or more storage devicesthrough a network, metadata indicative of organization of data within adata set, and map data indicative of organization of multiple datablocks within a data file maintained by the one or more storage devices,wherein the map data includes multiple map entries, and each map entryof the multiple map entries corresponds to one or more data blocks ofthe multiple data blocks; and receive, from multiple node devices,indications of which node devices among the multiple node devices areavailable node devices that are each able to perform a processing taskwith at least one data set portion of the one or more data set portions.In response to an indication within the metadata or the map data thatthe data set includes partitioned data wherein the data within the dataset is organized into multiple partitions that are each distributable toa single node device, and each map entry corresponds to a single datablock, the processor component may be caused to perform operationsincluding: determine a first quantity of the available node devicesbased on the indications of which node devices are available nodedevices; retrieve a second quantity of node devices last involved instorage of the data set within the data file from the metadata or themap data; compare the first and second quantities of node devices todetect a match between the first and second quantities; and assign eachof the available node devices one of a series of positive integer valuesas a designation value, wherein the series extends from an integer valueof 0 to a positive integer value equal to the first quantity minus theinteger value of 1. Additionally, in response to detection of a matchbetween the first and second quantities, for each map entry of the mapdata, the processor component may be caused to perform operationsincluding: retrieve, from the map entry, a hashed identifier for onedata sub-block indicated in the map entry as within the correspondingdata block, and a data sub-block size for each of the data sub-blocksindicated in the map entry as within the corresponding data block,wherein the hashed identifier is derived from a partition label of apartition of the multiple partitions and the data sub-block includes adata set portion of the one or more data set portions; determine alocation of the corresponding data block within the data file; dividethe hashed identifier by the first quantity to obtain a modulo value;compare the modulo value to the designation value assigned to each ofthe available node devices to identify an available node device assigneda designation value that matches the modulo value; and provide a pointerto the available node device assigned the designation value that matchesthe modulo value, the pointer including an indication of the location ofthe corresponding data block, and a sum of the data sub-block sizes ofall of the data sub-blocks within the corresponding data block.

In response to the indication that the data set includes partitioneddata and in response to detection of a lack of a match between the firstand second quantities, the processor component may, for each indicationwithin each map entry of a data sub-block within a corresponding datablock, be caused to perform operations including: retrieve, from the mapentry, the data sub-block size and hashed identifier of the datasub-block; determine a location of the data sub-block within the datafile; divide the hashed identifier by the first quantity to obtain amodulo value; compare the modulo value to the designation value assignedto each of the available node devices to identify an available nodedevice assigned a designation value that matches the modulo value; andprovide a pointer to the available node device assigned the designationvalue that matches the modulo value, wherein the pointer includes anindication of the location of the data sub-block and the data sub-blocksize.

In response to an indication within the metadata or the map data thatthe data set does not include partitioned data, for each map entry ofthe map data, the processor component may retrieve, from the map entry,a data block size and a data block quantity, wherein the data blockquantity indicates a quantity of adjacent data blocks in the data filethat correspond to the map entry. The processor component may also, foreach data block that corresponds to the map entry, perform operationsincluding: determine a location of the corresponding data block withinthe data file; select one of the available node devices; and provide apointer to the selected one of the available node devices, the pointerincluding an indication of the location of the corresponding data block,and the data block size. The selection of one of the available nodedevices may include a round robin selection of one of the available nodedevices.

The apparatus may include one of the available node devices. Theprocessor component may be caused to perform a processing task with atleast one data set portion retrieved from the data file as the one ofthe available node devices at least partially in parallel with at leastone other of the available node devices.

To retrieve the map data from the one or more storage devices, theprocessor component may be caused to perform operations including:retrieve a map base from the data file; analyze the map base todetermine whether at least a portion of the map data is stored withinone or more map extensions within the data file; and in response to adetermination that at least a portion of the map data is stored withinone or more map extensions, retrieve the one or more map extensions fromthe data file and retrieve at least a subset of the map entries from theone or more map extensions. In response to a determination that noportion of the map data is stored within one or more map extensions, theprocessor may be caused to retrieve all of the map entries from the mapbase.

To receive indications of which node devices among the multiple nodedevices are available, the processor component may be caused to performoperations including: recurringly receive indications of status from themultiple node devices; and recurringly update a stored indication of theavailability of each node device of the multiple node devices. Theprocessor component may be caused to perform operations includingprovide an indication of a task to perform with the data set to themultiple node devices to enable at least a first node device of themultiple node devices to perform the task with a first data set portionof the data set and at least a second node device of the multiple nodedevices to perform the task with a second data set portion of the dataset at least partially in parallel.

A computer-program product tangibly embodied in a non-transitorymachine-readable storage medium, the computer-program product includinginstructions operable to cause a processor component to performoperations including: retrieve, from one or more storage devices througha network, metadata indicative of organization of data within a dataset, and map data indicative of organization of multiple data blockswithin a data file maintained by the one or more storage devices,wherein the map data includes multiple map entries, and each map entryof the multiple map entries corresponds to one or more data blocks ofthe multiple data blocks; and receive, from multiple node devices,indications of which node devices among the multiple node devices areavailable node devices that are each able to perform a processing taskwith at least one data set portion of the one or more data set portions.In response to an indication within the metadata or the map data thatthe data set includes partitioned data wherein the data within the dataset is organized into multiple partitions that are each distributable toa single node device, and each map entry corresponds to a single datablock, the processor component may be caused to perform operationsincluding: determine a first quantity of the available node devicesbased on the indications of which node devices are available nodedevices; retrieve a second quantity of node devices last involved instorage of the data set within the data file from the metadata or themap data; compare the first and second quantities of node devices todetect a match between the first and second quantities; and assign eachof the available node devices one of a series of positive integer valuesas a designation value, wherein the series extends from an integer valueof 0 to a positive integer value equal to the first quantity minus theinteger value of 1. In response to detection of a match between thefirst and second quantities, for each map entry of the map data, theprocessor component may be caused to perform operations including:retrieve, from the map entry, a hashed identifier for one data sub-blockindicated in the map entry as within the corresponding data block, and adata sub-block size for each of the data sub-blocks indicated in the mapentry as within the corresponding data block, wherein the hashedidentifier is derived from a partition label of a partition of themultiple partitions and the data sub-block includes a data set portionof the one or more data set portions; determine a location of thecorresponding data block within the data file; divide the hashedidentifier by the first quantity to obtain a modulo value; compare themodulo value to the designation value assigned to each of the availablenode devices to identify an available node device assigned a designationvalue that matches the modulo value; and provide a pointer to theavailable node device assigned the designation value that matches themodulo value, wherein the pointer includes an indication of the locationof the corresponding data block and a sum of the data sub-block sizes ofall of the data sub-blocks within the corresponding data block.

In response to the indication that the data set includes partitioneddata and in response to detection of a lack of a match between the firstand second quantities, the processor component may, for each indicationwithin each map entry of a data sub-block within a corresponding datablock, perform operations including: retrieve, from the map entry, thedata sub-block size and hashed identifier of the data sub-block;determine a location of the data sub-block within the data file; dividethe hashed identifier by the first quantity to obtain a modulo value;compare the modulo value to the designation value assigned to each ofthe available node devices to identify an available node device assigneda designation value that matches the modulo value; and provide a pointerto the available node device assigned the designation value that matchesthe modulo value, wherein the pointer includes an indication of thelocation of the data sub-block and the data sub-block size.

In response to an indication within the metadata or the map data thatthe data set does not include partitioned data, for each map entry ofthe map data, the processor component may retrieve, from the map entry,a data block size and a data block quantity, wherein the data blockquantity indicates a quantity of adjacent data blocks in the data filethat correspond to the map entry. The processor component may also, foreach data block that corresponds to the map entry, perform operationsincluding: determine a location of the corresponding data block withinthe data file; select one of the available node devices; and provide apointer to the selected one of the available node devices, wherein thepointer includes an indication of the location of the corresponding datablock and the data block size. The selection of one of the availablenode devices includes a round robin selection of one of the availablenode devices. The processor component may be caused to employ, inresponse to the data set not including partitioned data, the indicationof the location and data block size of a data block corresponding to oneof the map entries to retrieve the data block from the data file as oneof the available node devices at least partially in parallel with atleast one other of the available node devices. The processor componentmay be caused to perform a processing task with the data block as theone of the available node devices at least partially in parallel with atleast one other of the available node devices.

To retrieve the map data from the one or more storage devices, theprocessor component may be caused to perform operations including:retrieve a map base from the data file; analyze the map base todetermine whether at least a portion of the map data is stored withinone or more map extensions within the data file; and in response to adetermination that at least a portion of the map data is stored withinone or more map extensions, retrieve the one or more map extensions fromthe data file and retrieve at least a subset of the map entries from theone or more map extensions. In response to a determination that noportion of the map data is stored within one or more map extensions, theprocessor component may be caused to perform operations includingretrieve all of the map entries from the map base.

To receive indications of which node devices among the multiple nodedevices are available, the processor component may be caused to performoperations including: recurringly receive indications of status from themultiple node devices; and recurringly update a stored indication of theavailability of each node device of the multiple node devices. Theprocessor component may be caused to perform operations including:provide an indication of a task to perform with the data set to themultiple node devices to enable at least a first node device of themultiple node devices to perform the task with a first data set portionof the data set; and perform the task with a second data set portion ofthe data set, as a second node device, at least partially in parallelwith the performance of the task by the first node device.

A computer-implemented method may include: retrieving, from one or morestorage devices through a network, metadata indicative of organizationof data within a data set, and map data indicative of organization ofmultiple data blocks within a data file maintained by the one or morestorage devices, wherein the map data includes multiple map entries andeach map entry of the multiple map entries corresponds to one or moredata blocks of the multiple data blocks; and receiving, from multiplenode devices, indications of which node devices among the multiple nodedevices are available node devices that are each able to perform aprocessing task with at least one data set portion of the one or moredata set portions. In response to an indication within the metadata orthe map data that the data set includes partitioned data wherein thedata within the data set is organized into multiple partitions that areeach distributable to a single node device, and each map entrycorresponds to a single data block, the method may include: determininga first quantity of the available node devices based on the indicationsof which node devices are available node devices; retrieving a secondquantity of node devices last involved in storage of the data set withinthe data file from the metadata or the map data; comparing the first andsecond quantities of node devices to detect a match between the firstand second quantities; and assigning each of the available node devicesone of a series of positive integer values as a designation value,wherein the series extends from an integer value of 0 to a positiveinteger value equal to the first quantity minus the integer value of 1.In response to detection of a match between the first and secondquantities, the method may include, for each map entry of the map data:retrieving, from the map entry, a hashed identifier for one datasub-block indicated in the map entry as within the corresponding datablock, and a data sub-block size for each of the data sub-blocksindicated in the map entry as within the corresponding data block,wherein the hashed identifier is derived from a partition label of apartition of the multiple partitions, and the data sub-block includes adata set portion of the one or more data set portions; determining alocation of the corresponding data block within the data file; dividingthe hashed identifier by the first quantity to obtain a modulo value;comparing the modulo value to the designation value assigned to each ofthe available node devices to identify an available node device assigneda designation value that matches the modulo value; and providing apointer to the available node device assigned the designation value thatmatches the modulo value, wherein the pointer includes an indication ofthe location of the corresponding data block and a sum of the datasub-block sizes of all of the data sub-blocks within the correspondingdata block.

In response to the indication that the data set includes partitioneddata and in response to detection of a lack of a match between the firstand second quantities, the method may include, for each indicationwithin each map entry of a data sub-block within a corresponding datablock: retrieving, from the map entry, the data sub-block size andhashed identifier of the data sub-block; determining a location of thedata sub-block within the data file; dividing the hashed identifier bythe first quantity to obtain a modulo value; comparing the modulo valueto the designation value assigned to each of the available node devicesto identify an available node device assigned a designation value thatmatches the modulo value; and providing a pointer to the available nodedevice assigned the designation value that matches the modulo value,wherein the pointer includes an indication of the location of the datasub-block and the data sub-block size.

In response to an indication within the metadata or the map data thatthe data set does not include partitioned data, the method may include,for each map entry of the map data, retrieving, from the map entry, adata block size and a data block quantity, wherein the data blockquantity indicates a quantity of adjacent data blocks in the data filethat correspond to the map entry. The method may also include, for eachdata block that corresponds to the map entry: determining a location ofthe corresponding data block within the data file; selecting one of theavailable node devices; and providing a pointer to the selected one ofthe available node devices, wherein the pointer includes an indicationof the location of the corresponding data block and the data block size.Selecting one of the available node devices may include a round robinselection of one of the available node devices.

In response to the data set including partitioned data, the method mayinclude acting as one of the available node devices by employing theindication of the location and data block size of a data blockcorresponding to one of the map entries to retrieve the data block fromthe data file at least partially in parallel with at least one other ofthe available node devices. The method may include performing aprocessing task with each data sub-block within the data block as theone of the available node devices at least partially in parallel with atleast one other of the available node devices.

Retrieving the map data from the one or more storage devices mayinclude: retrieving a map base from the data file; analyzing the mapbase to determine whether at least a portion of the map data is storedwithin one or more map extensions within the data file; and in responseto a determination that at least a portion of the map data is storedwithin one or more map extensions, retrieving the one or more mapextensions from the data file, and retrieving at least a subset of themap entries from the one or more map extensions. Retrieving the map datafrom the one or more storage devices may include, in response to adetermination that no portion of the map data is stored within one ormore map extensions, retrieving all of the map entries from the mapbase.

Receiving indications of which node devices among the multiple nodedevices are available may include: recurringly receiving indications ofstatus from the multiple node devices; and recurringly updating a storedindication of the availability of each node device of the multiple nodedevices. The method may include providing an indication of a task toperform with the data set to the multiple node devices to enable atleast a first node device of the multiple node devices to perform thetask with a first data set portion of the data set and at least a secondnode device of the multiple node devices to perform the task with asecond data set portion of the data set at least partially in parallel.

An apparatus may include a processor component and a storage to storeinstructions that, when executed by the processor component, may causethe processor component to perform operations including: receive, fromat least one node device of multiple node devices, at least a portion ofmetadata indicative of organization of data within a data set; receive,from the multiple node devices, indications of which node devices amongthe multiple node devices are to be involved in a storage of the dataset as multiple data blocks within a data file maintained by one or morestorage devices, wherein the organization of the multiple data blockswithin the data file is indicated in map data that includes multiple mapentries, and each map entry of the multiple map entries corresponds toone or more data blocks of the multiple data blocks; and receive, fromeach node device involved in the storage of the data set, a request fora pointer to a location within the data file at which the node device isto store at least one data set portion as a data block. In response toan indication received from the at least one node device that the dataset includes partitioned data, wherein the data within the data set isorganized into multiple partitions that are each distributable to asingle node device and each map entry corresponds to a single datablock, the processor component may be caused, for each request for apointer received from a node device involved in the storage of the dataset, to perform operations including: determine the location within thedata file at which the node device is to store the data block; generatea map entry within the map data that corresponds to the data block;generate within the map entry a data sub-block count indicative of aquantity of data sub-blocks to be stored by the node device within thedata block, wherein each data sub-block includes a data set portion ofthe data set that is to be stored by the node device; generate withinthe map entry a separate map sub-entry for each of the data sub-blocks,wherein each map sub-entry includes a sub-block size indicative of asize of a corresponding data set portion and a hashed identifier derivedfrom a partition label of the partition to which the corresponding dataset portion belongs; and provide a pointer to the node device, thepointer including an indication of the location at which the node deviceis to store the data block in the data file. In response to successfulstorage of all data blocks of the data set within the data file by allof the node devices involved in the storage of the data set, theprocessor component may be caused to store the map data in the datafile.

In response to a lack of indication received from the at least one nodedevice that the data set includes partitioned data, the processorcomponent may, for each request for a pointer received from a nodedevice involved in the storage of the data set, be caused to performoperations including: determine the location within the data file atwhich the node device is to store the data block; compare a data blocksize of the data block to a data block size indicated in the map datafor an adjacent data block to be stored by another node device of themultiple node devices at an adjacent location within the data file todetect a match between the two data block sizes; in response todetection of a match between the two data block sizes, increment a datablock count of a map entry within the map data that corresponds to theadjacent data block; in response to detection of a lack of a matchbetween the two data block sizes, generate a new map entry within themap data that corresponds to the data block, wherein the new map entryincludes a data block count indicative of correspondence to a singledata block and a data block size indicative of the size of the datablock; and provide a pointer to the node device, the pointer includingan indication of the location at which the node device is to store thedata block in the data file.

The at least a portion of the metadata may include the indicationreceived from the at least one node device that the data set includespartitioned data. Each node device involved in the storage of the dataset may be required to generate a single request for a pointer for thestorage of all data set portions distributed to the node device; and theprocessor component may be caused to determine that all pointers havebeen generated for the storage of all data set portions of the data setin the data file by all of the node devices involved in the storage ofthe data set based on reception of a single request for a pointer fromeach node device involved in the storage of the data set. The apparatusmay include one of the node devices involved in the storage of the dataset. To receive indications of which node devices among the multiplenode devices are involved in the storage of the data set within the datafile, the processor component may be caused to perform operationsincluding: recurringly receive indications of status from each nodedevice of the multiple node devices; and recurringly update a storedindication of whether each node device of the multiple node devices isinvolved in the storage of the data set.

To store the map data in the data file, the processor component may becaused to determine whether a size of the map data exceeds apredetermined data size. In response to a determination that the size ofthe map data exceeds the predetermined data size, the processorcomponent may also be caused to perform operations including: divide themap data into one or more map extensions; store the one or more mapextensions within the data file at locations dispersed among the datablocks stored by node devices involved in the storage of the data set;and store, within the data file, a map base including one or morepointers to the location of each map extension within the data file. Asize of each map extension stored within the data file at a locationfollowing a first one of the map extensions may be twice the size of apreceding map extension.

The processor component may be caused to perform operations includingprovide an indication of a task to perform with the data set to the nodedevices involved in the storage of the data set to enable at least afirst node device of the multiple node devices to perform the task witha first data set portion of the data set and at least a second nodedevice of the multiple node devices to perform the task with a seconddata set portion of the data set at least partially in parallel. Eachhashed identifier may include an integer value derived from a hash takenof a partition label that uniquely identifies one of the partitions ofthe multiple partitions.

A computer-program product tangibly embodied in a non-transitorymachine-readable storage medium, the computer-program product includinginstructions operable may cause a processor component to performoperations including: receive, from at least one node device of multiplenode devices, at least a portion of metadata indicative of organizationof data within a data set; receive, from the multiple node devices,indications of which node devices among the multiple node devices are tobe involved in a storage of the data set as multiple data blocks withina data file maintained by one or more storage devices, wherein theorganization of the multiple data blocks within the data file isindicated in map data that includes multiple map entries, and each mapentry of the multiple map entries corresponds to one or more data blocksof the multiple data blocks; and receive, from each node device involvedin the storage of the data set, a request for a pointer to a locationwithin the data file at which the node device is to store at least onedata set portion as a data block. In response to an indication receivedfrom the at least one node device that the data set includes partitioneddata, wherein the data within the data set is organized into multiplepartitions that are each distributable to a single node device and eachmap entry corresponds to a single data block, the processor componentmay be caused, for each request for a pointer received from a nodedevice involved in the storage of the data set, to perform operationsincluding: determine the location within the data file at which the nodedevice is to store the data block; generate a map entry within the mapdata that corresponds to the data block; generate within the map entry adata sub-block count indicative of a quantity of data sub-blocks to bestored by the node device within the data block, wherein each datasub-block includes a data set portion of the data set that is to bestored by the node device; generate within the map entry a separate mapsub-entry for each of the data sub-blocks, wherein each map sub-entryincludes a sub-block size indicative of a size of a corresponding dataset portion and a hashed identifier derived from a partition label ofthe partition to which the corresponding data set portion belongs; andprovide a pointer to the node device, the pointer including anindication of the location at which the node device is to store the datablock in the data file. In response to successful storage of all datablocks of the data set within the data file by all of the node devicesinvolved in the storage of the data set, the processor component may becaused to store the map data in the data file.

In response to a lack of indication received from the at least one nodedevice that the data set includes partitioned data, the processorcomponent may, for each request for a pointer received from a nodedevice involved in the storage of the data set, be caused to performoperations including: determine the location within the data file atwhich the node device is to store the data block; compare a data blocksize of the data block to a data block size indicated in the map datafor an adjacent data block to be stored by another node device of themultiple node devices at an adjacent location within the data file todetect a match between the two data block sizes; in response todetection of a match between the two data block sizes, increment a datablock count of a map entry within the map data that corresponds to theadjacent data block; in response to detection of a lack of a matchbetween the two data block sizes, generate a new map entry within themap data that corresponds to the data block, wherein the new map entryincludes a data block count indicative of correspondence to a singledata block and a data block size indicative of the size of the datablock; and provide a pointer to the node device, the pointer includingan indication of the location at which the node device is to store thedata block in the data file.

The at least a portion of the metadata may include the indicationreceived from the at least one node device that the data set includespartitioned data. Each node device involved in the storage of the dataset may be required to generate a single request for a pointer for thestorage of all data set portions distributed to the node device; and theprocessor component may be caused to determine that all pointers havebeen generated for the storage of all data set portions of the data setin the data file by all of the node devices involved in the storage ofthe data set based on reception of a single request for a pointer fromeach node device involved in the storage of the data set. The processorcomponent may be caused to perform operations including: request, as oneof the node devices involved in the storage of the data set, a pointerto a location within the data file at which to store at least one dataset portion as a data block; generate a pointer in response to therequest; and store, as one of the node devices involved in the storageof the data set, the at least one data set portion at a location withinthe data file indicated by the pointer at least partially in parallelwith storage of at least one other data set portion by another nodedevice involved in the storage of the data set. To receive indicationsof which node devices among the multiple node devices are involved inthe storage of the data set within the data file, the processorcomponent may be caused to perform operations including: recurringlyreceive indications of status from each node device of the multiple nodedevices; and recurringly update a stored indication of whether each nodedevice of the multiple node devices is involved in the storage of thedata set.

To store the map data in the file, the processor component may be causedto determine whether a size of the map data exceeds a predetermined datasize. In response to a determination that the size of the map dataexceeds the predetermined data size, the processor component may also becaused to: divide the map data into one or more map extensions; storethe one or more map extensions within the data file at locationsdispersed among the data blocks stored by node devices involved in thestorage of the data set; and store, within the data file, a map baseincluding one or more pointers to the location of each map extensionwithin the data file. A size of each map extension stored within thedata file at a location following a first one of the map extensions istwice the size of a preceding map extension.

The processor component may be caused to perform operations including:provide an indication of a task to perform with the data set to eachnode device involved in the storage of the data set to enable at least afirst node device involved in the storage of the data set to perform thetask with a first data set portion of the data set; and perform the taskwith a second data set portion of the data set, as a second node deviceinvolved in the storage of the data set, at least partially in parallelwith the performance of the task by the first node device. Each hashedidentifier may include an integer value derived from a hash taken of apartition label that uniquely identifies one of the partitions of themultiple partitions.

A computer-implemented method may include: receiving, from at least onenode device of multiple node devices via a network, at least a portionof metadata indicative of organization of data within a data set;receiving, from the multiple node devices via the network, indicationsof which node devices among the multiple node devices are to be involvedin a storage of the data set as multiple data blocks within a data filemaintained by one or more storage devices, wherein the organization ofthe multiple data blocks within the data file is indicated in map datathat includes multiple map entries, and each map entry of the multiplemap entries corresponds to one or more data blocks of the multiple datablocks; and receiving, from each node device involved in the storage ofthe data set via the network, a request for a pointer to a locationwithin the data file at which the node device is to store at least onedata set portion as a data block. In response to an indication receivedvia the network from the at least one node device that the data setincludes partitioned data, wherein the data within the data set isorganized into multiple partitions that are each distributable to asingle node device and each map entry corresponds to a single datablock, for each request for a pointer received from a node deviceinvolved in the storage of the data set, the method may include:determining the location within the data file at which the node deviceis to store the data block; generating a map entry within the map datathat corresponds to the data block; generating within the map entry adata sub-block count indicative of a quantity of data sub-blocks to bestored by the node device within the data block, wherein each datasub-block includes a data set portion of the data set that is to bestored by the node device; generating within the map entry a separatemap sub-entry for each of the data sub-blocks, wherein each mapsub-entry includes a sub-block size indicative of a size of acorresponding data set portion and a hashed identifier derived from apartition label of the partition to which the corresponding data setportion belongs; and providing a pointer to the node device via thenetwork, the pointer including an indication of the location at whichthe node device is to store the data block in the data file. In responseto successful storage of all data blocks of the data set within the datafile by all of the node devices involved in the storage of the data set,the method may include storing the map data in the data file.

In response to a lack of indication received from the at least one nodedevice that the data set includes partitioned data, the method mayinclude, for each request for a pointer received from a node deviceinvolved in the storage of the data set: determining the location withinthe data file at which the node device is to store the data block;comparing a data block size of the data block to a data block sizeindicated in the map data for an adjacent data block to be stored byanother node device of the multiple node devices at an adjacent locationwithin the data file to detect a match between the two data block sizes;in response to detecting a match between the two data block sizes,incrementing a data block count of a map entry within the map data thatcorresponds to the adjacent data block; in response to detecting a lackof a match between the two data block sizes, generating a new map entrywithin the map data that corresponds to the data block, wherein the newmap entry includes a data block count indicative of correspondence to asingle data block and a data block size indicative of the size of thedata block; and providing a pointer to the node device via the network,wherein the pointer includes an indication of the location at which thenode device is to store the data block in the data file.

At least a portion of the metadata may include the indication receivedfrom the at least one node device that the data set includes partitioneddata. Each node device involved in the storage of the data set may berequired to generate a single request for a pointer for the storage ofall data set portions distributed to the node device; and the method mayinclude determining that all pointers have been generated for thestorage of all data set portions of the data set in the data file by allof the node devices involved in the storage of the data set based onreceiving a single request for a pointer from each node device involvedin the storage of the data set. The method may include: requesting, asone of the node devices involved in the storage of the data set, apointer to a location within the data file at which to store at leastone data set portion as a data block; generating a pointer in responseto the requesting; and storing, as one of the node devices involved inthe storage of the data set, the at least one data set portion at alocation within the data file indicated by the pointer at leastpartially in parallel with storing of at least one other data setportion by another node device involved in the storage of the data set.Receiving indications of which node devices among the multiple nodedevices are involved in the storage of the data set within the data filemay include: recurringly receiving indications of status from each nodedevice of the multiple node devices via the network; and recurringlyupdating a stored indication of whether each node device of the multiplenode devices is involved in the storage of the data set.

Storing the map data in the file may include determining whether a sizeof the map data exceeds a predetermined data size. In response todetermining that the size of the map data exceeds the predetermined datasize, the method may also include: dividing the map data into one ormore map extensions; storing the one or more map extensions within thedata file at locations dispersed among the data blocks stored by nodedevices involved in the storage of the data set; and storing, within thedata file, a map base including one or more pointers to the location ofeach map extension within the data file. A size of each map extensionstored within the data file at a location following a first one of themap extensions may be twice the size of a preceding map extension.

The method may include providing an indication of a task to perform withthe data set to the node devices involved in the storage of the data setto enable at least a first node device of the multiple node devices toperform the task with a first data set portion of the data set and atleast a second node device of the multiple node devices to perform thetask with a second data set portion of the data set at least partiallyin parallel. Each hashed identifier may include an integer value derivedfrom a hash taken of a partition label that uniquely identifies one ofthe partitions of the multiple partitions.

An apparatus including a processor component and a storage to storeinstructions that, when executed by the processor component, cause theprocessor component to perform operations including: provide, to acontrol device, an indication of being currently available toparticipate in a performance of a processing task as a node device amongmultiple node devices; receive, from the control device, an indicationof the processing task to perform with one or more data set portions ofmultiple data set portions of a data set, wherein the data set includesdata organized in a manner indicated in metadata; perform the processingtask with the one or more data set portions; and provide a request tothe control device for a pointer to a location at which to store the oneor more data set portions as a data block of multiple data blocks withina data file maintained by one or more storage devices, wherein themultiple data blocks are organized within the data file in a mannerindicated in map data that includes multiple map entries, and each mapentry of the multiple map entries corresponds to one or more data blocksof the multiple data blocks. In response to an indication in themetadata that the data set includes partitioned data, wherein the datawithin the data set is organized into multiple partitions that are eachdistributable to a single node device and each map entry corresponds toa single data block, the processor component is caused to performoperations including: for each data set portion of the one or more dataset portions, include a data sub-block size indicative of a size of thedata set portion in the request, derive a hashed identifier of apartition label of the partition to which the data set portion belongsof the multiple partitions, and include the hashed identifier in therequest; receive, from the control device, the requested pointerindicating the location within the data file at which to store the datablock; and store each data set portion of the one or more data setportions as a data sub-block within the data block starting at thelocation within the data file.

In response to a lack of indication in the metadata that the data setincludes partitioned data, the processor component may be caused toperform operations including: derive a sum of sizes each data setportion of the one or more data set portions; include the sum of sizesas a data block size of the data block in the request; receive, from thecontrol device, the requested pointer indicating the location within thedata file at which to store the data block; and store the one or moredata set portions together as the data block at the location within thedata file. The processing task may include generation of the data set asan output, and the processor component may be caused to generate atleast a portion of the metadata and to provide the at least a portion ofthe metadata to the control device. The processing task includes use ofthe data set as an input; and the processor component may be caused toreceive the metadata from the control device.

The processor component may include multiple processor cores, and may becaused to perform the processing task with each data set portion of theone or more data set portions using a separate one of the multipleprocessor cores at least partially in parallel. The processor componentmay be caused to perform the processing task with at least one data setportion of the one or more data set portions at least partially inparallel with a performance, by at least one other node device of themultiple node devices, of the processing task with at least one otherdata set portion of the multiple data set portions. Each node device ofthe multiple node devices may be required to generate a single requestfor a pointer for all data set portions with which the processing taskis performed by each node device; and the processor component may becaused to generate the request to be associated with all of the data setportions of the one or more data set portions with which the processorcomponent performs the processing task.

The processor component may be caused to store the one or more dataportions within the data block within the data file at least partiallyin parallel with storage of at least one other data set portion of themultiple data set portions by at least one other node device of themultiple node devices. The processor component may be caused to, inresponse to completion of storage of the one or more data set portionswithin the data block within the data file, provide an indication of thecompletion of the storage to the control device.

The node device may include a separate and distinct device from any ofthe one or more storage devices; the node device includes the controldevice implemented as a controller within the node device; and thecontroller includes a controller processor component and a controllerstorage to store controller instructions that, when executed by thecontroller processor component, cause the controller processor componentto perform operations including determine the location within the datafile at which to store the data block indicated by the requestedpointer, and provide the requested pointer to the processor component.In response to the indication in the metadata that the data set includespartitioned data, the controller processor component may be caused to:generate a map entry within the map data that corresponds to the datablock; generate within the map entry a data sub-block count indicativeof a quantity of data sub-blocks to be stored by the node device withinthe data block, wherein each data sub-block includes a data set portionof the one or more data set portions; and generate within the map entrya separate map sub-entry for each of the data sub-blocks, wherein eachmap sub-entry includes a sub-block size indicative of a size of acorresponding data set portion and a hash identifier derived from apartition label of the partition to which the corresponding data setportion belongs. In response to generation of all pointers for thestorage of all data set portions of the data set in the data file by allof the multiple node devices, the controller processor component mayalso be caused to store the map data in the data file. In response to alack of indication in the metadata that the data set includespartitioned data, the controller processor component may be caused toperform operations including: compare a data block size of the datablock to a data block size of an adjacent data block to be stored byanother node device of the multiple node devices at an adjacent locationwithin the data file to detect a match between the two data block sizes;in response to detection of a match between the two data block sizes,increment a data block count of a map entry within the map data thatcorresponds to the adjacent data block; and in response to detection ofa lack of a match between the two data block sizes, generate a new mapentry within the map data that corresponds to the data block, whereinthe new map entry includes a data block count indicative ofcorrespondence to a single data block and a data block size indicativeof the size of the data block.

A computer-program product tangibly embodied in a non-transitorymachine-readable storage medium, the computer-program product includinginstructions operable to cause a processor component to performoperations including: provide, to a control device, an indication ofbeing currently available to participate in a performance of aprocessing task as a node device among multiple node devices; receive,from the control device, an indication of the processing task to performwith one or more data set portions of multiple data set portions of adata set, wherein the data set includes data organized in a mannerindicated in metadata; perform the processing task with the one or moredata set portions; and provide a request to the control device for apointer to a location at which to store the one or more data setportions as a data block of multiple data blocks within a data filemaintained by one or more storage devices, wherein the multiple datablocks are organized within the data file in a manner indicated in mapdata that includes multiple map entries, and each map entry of themultiple map entries corresponds to one or more data blocks of themultiple data blocks. In response to an indication in the metadata thatthe data set includes partitioned data, wherein the data within the dataset is organized into multiple partitions that are each distributable toa single node device and each map entry corresponds to a single datablock, the processor component may caused to perform operationsincluding: for each data set portion of the one or more data setportions, include a data sub-block size indicative of a size of the dataset portion in the request, derive a hashed identifier of a partitionlabel of the partition to which the data set portion belongs of themultiple partitions, and include the hashed identifier in the request;receive, from the control device, the requested pointer indicating thelocation within the data file at which to store the data block; andstore each data set portion of the one or more data set portions as adata sub-block within the data block starting at the location within thedata file.

In response to a lack of indication in the metadata that the data setincludes partitioned data, the processor component may be caused toperform operations including: derive a sum of sizes each data setportion of the one or more data set portions; include the sum of sizesas a data block size of the data block in the request; receive, from thecontrol device, the requested pointer indicating the location within thedata file at which to store the data block; and store the one or moredata set portions together as the data block at the location within thedata file. The processing task may include generation of the data set asan output, and the processor component may be caused to generate atleast a portion of the metadata and to provide the at least a portion ofthe metadata to the control device. The processing task includes use ofthe data set as an input, and the processor component may be caused toreceive the metadata from the control device.

The processor component may be caused to perform the processing taskwith each data set portion of the one or more data set portions using aseparate one of multiple processor cores of the processor component atleast partially in parallel. The processor component may be caused toperform the processing task with at least one data set portion of theone or more data set portions at least partially in parallel with aperformance, by at least one other node device of the multiple nodedevices, of the processing task with at least one other data set portionof the multiple data set portions. Each node device of the multiple nodedevices may be required to generate a single request for a pointer forall data set portions with which the processing task is performed byeach node device; and the processor component may be caused to generatethe request to be associated with all of the data set portions of theone or more data set portions with which the processor componentperforms the processing task.

The processor component may be caused to store the one or more dataportions within the data block within the data file at least partiallyin parallel with storage of at least one other data set portion of themultiple data set portions by at least one other node device of themultiple node devices. The processor component may be caused to, inresponse to completion of storage of the one or more data set portionswithin the data block within the data file, provide an indication of thecompletion of the storage to the control device.

A computer-implemented method may include: providing, to a controldevice, an indication of being currently available to participate in aperformance of a processing task as a node device among multiple nodedevices; receiving, from the control device, an indication of theprocessing task to perform with one or more data set portions ofmultiple data set portions of a data set, wherein the data set includesdata organized in a manner indicated in metadata; performing theprocessing task with the one or more data set portions; and providing arequest to the control device for a pointer to a location at which tostore the one or more data set portions as a data block of multiple datablocks within a data file maintained by one or more storage devices,wherein the multiple data blocks are organized within the data file in amanner indicated in map data that includes multiple map entries, andeach map entry of the multiple map entries corresponds to one or moredata blocks of the multiple data blocks. In response to an indication inthe metadata that the data set includes partitioned data, wherein thedata within the data set is organized into multiple partitions that areeach distributable to a single node device and each map entrycorresponds to a single data block, the method may include: for eachdata set portion of the one or more data set portions, including, in therequest, a data sub-block size indicative of a size of the data setportion, derive a hashed identifier of a partition label of thepartition to which the data set portion belongs of the multiplepartitions, and including, in the request, the hashed identifier;receiving, from the control device, the requested pointer indicating thelocation within the data file at which to store the data block; andstoring each data set portion of the one or more data set portions as adata sub-block within the data block starting at the location within thedata file.

In response to a lack of indication in the metadata that the data setincludes partitioned data, the method may include: deriving a sum ofsizes each data set portion of the one or more data set portions;including the sum of sizes as a data block size of the data block in therequest; receiving, from the control device, the requested pointerindicating the location within the data file at which to store the datablock; and storing the one or more data set portions together as thedata block at the location within the data file. The processing task mayinclude generation of the data set as an output, and the method mayinclude generating at least a portion of the metadata and to provide theat least a portion of the metadata to the control device. The processingtask may include use of the data set as an input, and the method mayinclude includes receiving the metadata from the control device.

The method may include performing the processing task with each data setportion of the one or more data set portions using a separate one ofmultiple processor cores of a processor component of the node device atleast partially in parallel. The method may include performing theprocessing task with at least one data set portion of the one or moredata set portions at least partially in parallel with a performance, byat least one other node device of the multiple node devices, of theprocessing task with at least one other data set portion of the multipledata set portions. Each node device of the multiple node devices may berequired to generate a single request for a pointer for all data setportions with which the processing task is performed by each nodedevice; and the method may include generating the request to beassociated with all of the data set portions of the one or more data setportions with which the processor component performs the processingtask.

The method may include storing the one or more data portions within thedata block within the data file at least partially in parallel withstorage of at least one other data set portion of the multiple data setportions by at least one other node device of the multiple node devices.The method may include, in response to completion of storage of the oneor more data set portions within the data block within the data file,providing an indication of the completion of the storage to the controldevice.

The foregoing, together with other features and embodiments, will becomemore apparent upon referring to the following specification, claims, andaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is described in conjunction with the appendedfigures:

FIG. 1 illustrates a block diagram that provides an illustration of thehardware components of a computing system, according to some embodimentsof the present technology.

FIG. 2 illustrates an example network including an example set ofdevices communicating with each other over an exchange system and via anetwork, according to some embodiments of the present technology.

FIG. 3 illustrates a representation of a conceptual model of acommunications protocol system, according to some embodiments of thepresent technology.

FIG. 4 illustrates a communications grid computing system including avariety of control and worker nodes, according to some embodiments ofthe present technology.

FIG. 5 illustrates a flow chart showing an example process for adjustinga communications grid or a work project in a communications grid after afailure of a node, according to some embodiments of the presenttechnology.

FIG. 6 illustrates a portion of a communications grid computing systemincluding a control node and a worker node, according to someembodiments of the present technology.

FIG. 7 illustrates a flow chart showing an example process for executinga data analysis or processing project, according to some embodiments ofthe present technology.

FIG. 8 illustrates a block diagram including components of an EventStream Processing Engine (ESPE), according to embodiments of the presenttechnology.

FIG. 9 illustrates a flow chart showing an example process includingoperations performed by an event stream processing engine, according tosome embodiments of the present technology.

FIG. 10 illustrates an ESP system interfacing between a publishingdevice and multiple event subscribing devices, according to embodimentsof the present technology.

FIGS. 11A and 11B each illustrate an example embodiment of a distributedprocessing system.

FIGS. 12A, 12B and 12C each illustrate an example embodiment ofdistribution of portions of a data set.

FIGS. 13A, 13B, 13C, 13D and 13E, together, illustrate an example ofstoring portions of non-partitioned data of a data set.

FIGS. 14A, 14B, 14C, 14D and 14E, together, illustrate an example ofretrieving non-partitioned data of a data set.

FIGS. 15A, 15B, 15C, 15D and 15E, together, illustrate an example ofstoring portions of partitioned data of a data set.

FIGS. 16A, 16B, 16C and 16D, together, illustrate an example ofretrieving partitioned data of a data set.

FIG. 17 illustrates an example embodiment of a logic flow of a nodedevice storing data set portions.

FIG. 18 illustrates an example embodiment of a logic flow of a noderetrieving data set portions.

FIGS. 19A and 19B, together, illustrate an example embodiment of a logicflow of a control device coordinating storage of data set portions.

FIGS. 20A, 20B and 20C, together, illustrate an example embodiment of alogic flow of a control device coordinating retrieval of data setportions.

DETAILED DESCRIPTION

Various embodiments described herein are generally directed tointer-device coordination and data set organization to improvedistributed storage and retrieval of a data set processed by multiplenode devices. A data set may be stored within a single data file forrelatively long term storage (also commonly referred to as “persisted”)in a distributed manner among one or more storage devices. The data ofthe data set may be divided into multiple data blocks and/or datasub-blocks within the data file in a manner that correlates to themanner in which portions of the data set are distributed among multiplenode devices during processing. The data file may include a map of themanner in which the data blocks and/or data sub-blocks are organizedwithin the single data file, including the quantity, size(s) and/orlocation(s) within the data file. The one or more storage devices mayemploy any of a variety of file systems to store the data file, and thedata file may include a file header providing indications of variouscharacteristics of the data file relevant to that file system. It shouldbe noted that the manner in which the data file is distributed among theone or more storage devices may be entirely unrelated to the manner inwhich the data of the data set is divided into data blocks. By way ofexample, the manner in which the data of the data set is divided intodata blocks advantageously does not affect or preclude the distributionof the data file among multiple storage devices configured to cooperateto form a redundant array of inexpensive disks (RAID) array to provideprotection against loss of the data file and/or to provide faster accessto the data file.

The data within the data set may be organized in any of a variety ofways (e.g., rows and columns, columnar, one or more hypercubes, etc.)with any of a variety of indexing mechanisms that may employ any of avariety of labeling schemes. To enable access to and use of the data,the data set may include metadata that is descriptive of such aspects ofthe manner in which the data of the data set is so organized. In someembodiments, the data within the data set may be organized into multiplepartitions in which the data within each partition is required beprocessed all together as a single atomic unit. Therefore, if the dataset is partitioned, the data blocks, and the one or more data sub-blocksinto which each data block may be divided, may be at least partiallydefined by the manner in which data is organized into partitions. Aswill be explained in greater detail, the manner in which the data set isstored within the data file by the multiple node devices and the mannerin which the data set is retrieved by the multiple node devices may beat least partially dependent on whether the data of the data set ispartitioned. The metadata and/or the map may include an indication ofwhether the data of the data set is partitioned, and if so, the metadatamay describe various aspects of the partitioning. Partitioning of thedata within a data set may aid in simplifying and optimizing processingin a distributed multi-node computational environment, by serving as amechanism by which logically-related data are physically groupedtogether for processing on the same node device. Co-locating all datawithin a partition on the same node device may eliminate the need fortime-consuming and/or resource-consuming inter-node data shuffling ascomputations are done on the partition data as a whole. Furthermore, astraightforward scheme may be used to locate the specific node devicecontaining the partition which will be explained in greater detailherein.

The actions taken by the multiple node devices to store and retrieve thedata set may be coordinated thereamong by a control device. In someembodiments, the control device may be separate and distinct from all ofthe node devices. In other embodiments, such a coordinating function ofthe control device may be performed by one of the multiple node devices(e.g., on a separate execution thread, by a separate processor core,within a separate virtual machine, etc.). In storing or retrieving thedata set, the control device and each node device of the multiple nodedevices may directly access the single data file in which the data setis stored. More specifically, the control device may directly store orretrieve the metadata and the map, while each of the node devices maydirectly store or retrieve one or more different data blocks and/or datasub-blocks. At least the accesses made by the node devices to store orretrieve data blocks and/or data sub-blocks may be performed at leastpartially in parallel. The control device may provide each of the nodedevices with one or more pointers to locations within the data file atwhich the different data blocks and/or data sub-blocks may be stored orretrieved in the form of offsets relative to a designated startinglocation of the data file (e.g., offsets from the first byte of the datafile or from the first byte of a payload portion of the data file).Through such use of pointers, the need for coordination between the nodedevices and the control device is greatly minimized. The node devicesare each able to separately act to store or retrieve data block(s)and/or data sub-block(s) without the need to synchronize the timing ofsuch acts with each other and/or with the control device. In someembodiments, the control device may store or retrieve the metadataand/or the map at least partially in parallel with the storage orretrieval, respectively, of data blocks and/or data sub-blocks performedby one or more of the multiple node devices.

In embodiments in which the data of the data set is not partitioned, themap may include indications of the size of each data block and/or howmany data blocks are used to store the data of the data set. To reducestorage requirements for the map, itself, the map may include a table orsimilar data structure of multiple entries in which each entry includesan indication of a data block size and a quantity of how many datablocks stored adjacently within the data file share that data blocksize. In embodiments in which the data of the data set is partitioned,the map may include entries for each data block in which each entryindicates sizes and hashed identifiers for each of the one or more datasub-blocks within each data block. As will be explained in greaterdetail, each partition may have a unique partition label that may bedescribed in the metadata and/or may be included with the data belongingto that partition, and a hash may be taken of each such partition labelto generate a corresponding hashed identifier. Depending on the storagerequirements for the map, itself, the map may be stored entirely withina single location within data file, or portions of the map may be storedat multiple locations distributed within the data file.

In storing the data set within the data file in embodiments in which thedata of the data set is not partitioned, each of the node devices maytransmit a request to the control device for a pointer to a locationwithin the data file at which to store a data block. Each such requestmay include an indication of the size of the data block that therequesting node device is to store at that location. The specificationof the size of the data block to be stored in each request enables thecontrol device to derive the location within the data file to specify inthe next pointer that the control device provides in response to thenext request for a pointer from another node device. The control devicemay also employ the specified size to add an indication to the map ofthe data block to be stored by the requesting node device. Each nodedevice that so requests a pointer, upon being provided with therequested pointer, may employ the pointer to store the data block forwhich the pointer was requested. Such requesting and provision ofpointers at which to store data blocks within the data file may continueuntil there are no more data blocks of the data set to be stored by anyof the node devices for which a pointer has not been requested. In someembodiments, each of the node devices may transmit an indication to thecontrol device of having no more data blocks of the data set to requestpointers for. However, in other embodiments in which each of the nodedevices is required to request only a single pointer for all data thatis to be stored by that node device, the control device may determinewhether there are more data blocks for which pointers remain to berequested based on whether or not requests for pointers have beenreceived from all of the node devices involved in processing the dataset. In some embodiments, the control device may store the map and/orthe metadata of the data set within the data file in response to therebeing no more data blocks of the data set for which pointers need to berequested. In such embodiments, the storage of the map and/or themetadata by the control device is thereby not dependent upon, and neednot be synchronized with, the storage of any of the data blocks and/ordata sub-blocks performed by the node devices. However, in otherembodiments, the control device may delay storage of the map and/ormetadata of the data set within the data file until indications havebeen received by the control device from all of the node devices thatall of the data blocks have been successfully stored. This may be deemeddesirable as a measure to address errors in transmission of one or moredata blocks to the one or more storage devices via a network and/orerrors in storage of one or more data blocks by the one or more storagedevices.

In embodiments in which the data of the data set is not partitioned, thelack of a requirement to keep any two or more specific portions of thedata of the data set together for processing may result in the divisionof the data of the data set into data blocks being correlated solely tothe manner in which the data of the data set was distributed among themultiple node devices at the time the data set was generated and/or mostrecently stored. More specifically, each data block stored within thedata file is stored therein by only one node device such that no datablock within the data file includes data stored therein by more than onenode device. However, in some embodiments, a single node device maystore more than one data block within the data file such that a singlenode may request more than one pointer from the control device. In someembodiments, this may arise as a result of a distribution of data and ofprocessing of the data among multiple execution threads, multiplevirtual machines and/or multiple processor cores within a single nodedevice. Thus, for each portion of the data within a single node devicehas been fully processed within and/or by a separate correspondingexecution thread, virtual machine and/or processor core, the node devicemay make a separate request for a separate pointer to a location withinthe data file at which a separate corresponding data block is to bestored. Alternatively, a single request for a single pointer at which tocontiguously store all of the data blocks associated with a single nodedevice may be requested, and the request may specify a size that is sumof the sizes of all of those data blocks. This may be the case inembodiments in which each node device is required to make only onerequest for a pointer. However, as an alternative to such a singlerequest specifying a size that is the sum of the sizes of all of thedata blocks to be stored by a node device, the request alternatively mayinclude specifications of a separate size for each data block.

In retrieving the data set from the data file in embodiments in whichthe data of the data set is not partitioned, the control device mayretrieve indications of which node devices are available to performprocessing on the data set. In some embodiments, the quantity of nodedevices that are available may vary with time based on any of a varietyof factors, including demands for the processing resources of each ofthe node devices to perform other processing tasks, user sessions thatindicate a specific node device count based on policy, known performancecharacteristics, service-level agreements, etc., instances of nodedevices having malfunctioned or being taken out of service for otherreasons, etc. The control device may then access the data file toretrieve the map and the metadata of the data set, and may relay anindication of a task to be performed and/or the metadata to each of theavailable ones of the multiple node devices. The control device may thenemploy the information concerning each data block within the map todistribute the data blocks among the available node devices. The controldevice may employ any of a variety of techniques to distribute the datablocks among the available ones of the node devices, from simpler roundrobin techniques to any of a variety of data size balancing techniques.

In effecting this distribution of the data blocks, for each data blockthat the control device assigns to a node device, the control device maytransmit a pointer to the location of the data block within the datafile to the node device, along with an indication of the size of thedata block. For each such combination of pointer and size of a datablock received by a node device, the node device may employ the pointerto access and retrieve the data block from within the data file,starting at the location pointed to by the pointer and ceasing when theamount of data of the data block indicated by the size has beenretrieved. In some embodiments, each node device may transmit anindication to the control device of having completed each such retrievalof a data block. As each node device to which the retrieval of one ormore data blocks has been assigned completes the retrieval of theassigned one or more data blocks, the node device may begin performingprocessing tasks with the assigned one or more data blocks. Again,through such use of pointers, the need for coordination among the nodedevices and/or between the node devices and the control device isgreatly minimized More specifically, there may be no synchronization ofwhen each node begins performing processing tasks with the one or moredata blocks assigned to it, such that each node may immediately beginsuch processing upon retrieving at least a portion of at least one datablock.

Various aspects of storing the data set within the data file inembodiments in which the data of the data set is partitioned may differfrom storing the data set in embodiments in which the data of the dataset is not partitioned. Each of the node devices may transmit a requestto the control device for a pointer to a location within the data fileat which to store a single data block that includes one or more datasub-blocks. Each such request may include a data structure providingindications of the quantity of data sub-blocks, the size of each datasub-block and/or the hashed identifier of each data sub-block. Thespecifications of the quantity of data sub-blocks within each data blockand the size of each data sub-block enables the control device to derivethe location within the data file to specify in the next pointer thatthe control device provides in response to the next request for apointer from this or another node device. The control device may alsoemploy such information, as well as the hashed identifiers, in addingindications of the data block and of the one or more data sub-blockstherein to the map. Each node device that so requests a pointer, uponbeing provided with the requested pointer, may employ the pointer tostore the data block for which the pointer was requested as part of thedata file. As each node device receives pointer for the data block thatit is to store, each node device may transmit an indication to thecontrol device of having no more data blocks to request pointers for.However, in embodiments in which each of the node devices is required torequest only a single pointer for all data that is to be stored by thatnode device, the control device may determine whether there are moredata blocks for which pointers remain to be requested based on whetheror not requests for pointers have been received from all of the nodedevices involved in processing the data set. In response to there beingno more data blocks of the data set for which any of the node devicesneed to be provided with a pointer, the control device may store themap, the metadata of the data set and/or a data header within the datafile. The data header may include an indication of how many node deviceswere involved in generating the data set and/or in storing the data setfollowing its generation.

As previously discussed, in embodiments in which the data of the dataset is partitioned, all of the data within each partition may berequired to be processed together within a single node device, and notdistributed among multiple node devices. However, a single node devicemay perform processing operations involving the data of more than onepartition. As also previously discussed, all of the data within eachpartition must be stored together within a single data block within thedata file, and not distributed among multiple data blocks within thedata file. However, within each data block, the data of a singlepartition may be divided into multiple data sub-blocks, and a singledata block may include data sub-blocks of the data of more than onepartition. The hashed identifiers associated with each data sub-block bythe map may be employed by the control device to distinguish between themultiple partitions to which the data within each data sub-blockbelongs.

Various aspects of retrieving the data set from the data file inembodiments in which the data of the data set is partitioned may differfrom retrieving the data set in embodiments in which the data of thedata set is not partitioned. The control device may retrieve indicationsof which node devices are available to perform processing on the dataset. Again, in some embodiments, the quantity of available node devicesmay vary over time. The control device may access the data file toretrieve the map, the metadata of the data set and/or the data header.The control device may then transmit an indication of a task to performwith the data set and/or the metadata to each of the available ones ofthe multiple node devices. The control device may then employ acombination of the hashed identifiers associated with the datasub-blocks, the quantity of partitions into which the data set isdivided, the quantity of node devices involved in generating and/or inmost recently storing the data set within the data file, and thequantity of node devices that are currently available in deriving adistribution of the data blocks and/or data sub-blocks of the data setamong the currently available node devices.

More specifically, the control device may compare the quantity of nodedevices involved in the most recent storage of the data set within thedata file to the quantity of currently available node devices. If thesetwo quantities of node devices match, then the control device maydistribute the data blocks among the currently available node devices ina manner that recreates the distribution of partitions among nodedevices that existed at the time the data set was most recently storedwithin the data file. To effect this distribution of partitions amongthe currently available node devices, the control device may provideeach currently available node device with at least one pointer to alocation within the data file from which the node device may retrieve adata block, along with an indication of the size of the data block.Thus, distribution of the pointers, and accordingly, of the data of thedata set, is based on the data blocks within the data file, therebyavoiding the time and/or data transmission overhead of distributing whatmay be a considerably greater quantity of pointers to individual datasub-blocks.

However, if the quantity of node devices involved in at least storingthe data set within the data file does not match the quantity ofcurrently available node devices, then the control device may distributethe data sub-blocks among the currently available node devices using anyof a variety of techniques, while ensuring that there are no instancesin which the data of any partition is distributed among multiple nodedevices. In so doing, the control device may employ the hashedidentifier associated by the map with each individual data sub-block. Byway of example, the control device may divide each of the hashedidentifiers by the quantity of currently available node devices toderive the modulo value from each such division. The control device maythen employ the modulo value as the indicator of which node device todistribute each data sub-block to. To effect this distribution ofpartitions among the currently available node devices, the controldevice may provide each currently available node device with at leastone pointer to a location within the data file from which the nodedevice may retrieve a data sub-block, along with an indication of thesize of the data sub-block. Such a distribution of pointers to locationsof individual data sub-blocks within data blocks, instead of adistribution of pointers to locations of data blocks, may be performedin recognition of the fact that a single data block may include datasub-blocks associated with more than one partition.

For each such combination of pointer and size of a data block or a datasub-block received by a node device, the node device may employ thepointer to access and retrieve the data block or data sub-block withinthe data file, starting at the location pointed to by the pointer andceasing when the amount of data of the data block or the data sub-blockindicated by the size has been retrieved. In some embodiments, each nodedevice may transmit an indication to the control device of havingcompleted the retrieval of each data block or data sub-block. As eachnode device to which one or more data blocks or data sub-blocks has beenassigned completes the retrieval of those one or more data blocks ordata sub-blocks, the node device may begin performing a processing taskwith the data of those data blocks or data sub-blocks. Alternatively, anode device may begin performance of a processing task even as the nodecontinues to retrieve those one or more data blocks or data sub-blocks.

In various embodiments, the control device and the multiple node devicesmay cooperate to provide security for the data of the data set. In someembodiments, the control device may encrypt the metadata and/or the mapprior to storage within the data file during storage of the data setwithin the data file. Correspondingly, the control device may decryptthe metadata and/or map prior to providing the metadata and/or pointersto the node devices during retrieval of the data set from the data file.In some embodiments, the node devices may encrypt the data blocks and/orthe data sub-blocks during storage of the data set within the data file,and/or may decrypt the data blocks and/or the data sub-blocks duringretrieval of the data set from the data file. In support of suchencryption and/or decryption by the node devices, the control device maydistribute one or more security credentials employed in such encryptionand/or decryption among the node devices. Alternatively or additionally,the control device may store indications of such security credentialswithin the data file during storage of the data set therein and/or mayretrieve those indications from the data file during retrieval of thedata set therefrom.

With general reference to notations and nomenclature used herein,portions of the detailed description that follows may be presented interms of program procedures executed by a processor component of amachine or of multiple networked machines. These procedural descriptionsand representations are used by those skilled in the art to mosteffectively convey the substance of their work to others skilled in theart. A procedure is here, and generally, conceived to be aself-consistent sequence of operations leading to a desired result.These operations are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical, magnetic or optical communications capable of beingstored, transferred, combined, compared, and otherwise manipulated. Itproves convenient at times, principally for reasons of common usage, torefer to what is communicated as bits, values, elements, symbols,characters, terms, numbers, or the like. It should be noted, however,that all of these and similar terms are to be associated with theappropriate physical quantities and are merely convenient labels appliedto those quantities.

Further, these manipulations are often referred to in terms, such asadding or comparing, which are commonly associated with mentaloperations performed by a human operator. However, no such capability ofa human operator is necessary, or desirable in most cases, in any of theoperations described herein that form part of one or more embodiments.Rather, these operations are machine operations. Useful machines forperforming operations of various embodiments include machinesselectively activated or configured by a routine stored within that iswritten in accordance with the teachings herein, and/or includeapparatus specially constructed for the required purpose. Variousembodiments also relate to apparatus or systems for performing theseoperations. These apparatus may be specially constructed for therequired purpose or may include a general purpose computer. The requiredstructure for a variety of these machines will appear from thedescription given.

Reference is now made to the drawings, wherein like reference numeralsare used to refer to like elements throughout. In the followingdescription, for purposes of explanation, numerous specific details areset forth in order to provide a thorough understanding thereof. It maybe evident, however, that the novel embodiments can be practiced withoutthese specific details. In other instances, well known structures anddevices are shown in block diagram form in order to facilitate adescription thereof. The intention is to cover all modifications,equivalents, and alternatives within the scope of the claims.

Systems depicted in some of the figures may be provided in variousconfigurations. In some embodiments, the systems may be configured as adistributed system where one or more components of the system aredistributed across one or more networks in a cloud computing systemand/or a fog computing system.

FIG. 1 is a block diagram that provides an illustration of the hardwarecomponents of a data transmission network 100, according to embodimentsof the present technology. Data transmission network 100 is aspecialized computer system that may be used for processing largeamounts of data where a large number of computer processing cycles arerequired.

Data transmission network 100 may also include computing environment114. Computing environment 114 may be a specialized computer or othermachine that processes the data received within the data transmissionnetwork 100. Data transmission network 100 also includes one or morenetwork devices 102. Network devices 102 may include client devices thatattempt to communicate with computing environment 114. For example,network devices 102 may send data to the computing environment 114 to beprocessed, may send signals to the computing environment 114 to controldifferent aspects of the computing environment or the data it isprocessing, among other reasons. Network devices 102 may interact withthe computing environment 114 through a number of ways, such as, forexample, over one or more networks 108. As shown in FIG. 1, computingenvironment 114 may include one or more other systems. For example,computing environment 114 may include a database system 118 and/or acommunications grid 120.

In other embodiments, network devices may provide a large amount ofdata, either all at once or streaming over a period of time (e.g., usingevent stream processing (ESP), described further with respect to FIGS.8-10), to the computing environment 114 via networks 108. For example,network devices 102 may include network computers, sensors, databases,or other devices that may transmit or otherwise provide data tocomputing environment 114. For example, network devices may includelocal area network devices, such as routers, hubs, switches, or othercomputer networking devices. These devices may provide a variety ofstored or generated data, such as network data or data specific to thenetwork devices themselves. Network devices may also include sensorsthat monitor their environment or other devices to collect dataregarding that environment or those devices, and such network devicesmay provide data they collect over time. Network devices may alsoinclude devices within the internet of things, such as devices within ahome automation network. Some of these devices may be referred to asedge devices, and may involve edge computing circuitry. Data may betransmitted by network devices directly to computing environment 114 orto network-attached data stores, such as network-attached data stores110 for storage so that the data may be retrieved later by the computingenvironment 114 or other portions of data transmission network 100.

Data transmission network 100 may also include one or morenetwork-attached data stores 110. Network-attached data stores 110 areused to store data to be processed by the computing environment 114 aswell as any intermediate or final data generated by the computing systemin non-volatile memory. However in certain embodiments, theconfiguration of the computing environment 114 allows its operations tobe performed such that intermediate and final data results can be storedsolely in volatile memory (e.g., RAM), without a requirement thatintermediate or final data results be stored to non-volatile types ofmemory (e.g., disk). This can be useful in certain situations, such aswhen the computing environment 114 receives ad hoc queries from a userand when responses, which are generated by processing large amounts ofdata, need to be generated on-the-fly. In this non-limiting situation,the computing environment 114 may be configured to retain the processedinformation within memory so that responses can be generated for theuser at different levels of detail as well as allow a user tointeractively query against this information.

Network-attached data stores may store a variety of different types ofdata organized in a variety of different ways and from a variety ofdifferent sources. For example, network-attached data storage mayinclude storage other than primary storage located within computingenvironment 114 that is directly accessible by processors locatedtherein. Network-attached data storage may include secondary, tertiaryor auxiliary storage, such as large hard drives, servers, virtualmemory, among other types. Storage devices may include portable ornon-portable storage devices, optical storage devices, and various othermediums capable of storing, containing data. A machine-readable storagemedium or computer-readable storage medium may include a non-transitorymedium in which data can be stored and that does not include carrierwaves and/or transitory electronic signals. Examples of a non-transitorymedium may include, for example, a magnetic disk or tape, opticalstorage media such as compact disk or digital versatile disk, flashmemory, memory or memory devices. A computer-program product may includecode and/or machine-executable instructions that may represent aprocedure, a function, a subprogram, a program, a routine, a subroutine,a module, a software package, a class, or any combination ofinstructions, data structures, or program statements. A code segment maybe coupled to another code segment or a hardware circuit by passingand/or receiving information, data, arguments, parameters, or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, amongothers. Furthermore, the data stores may hold a variety of differenttypes of data. For example, network-attached data stores 110 may holdunstructured (e.g., raw) data, such as manufacturing data (e.g., adatabase containing records identifying products being manufactured withparameter data for each product, such as colors and models) or productsales databases (e.g., a database containing individual data recordsidentifying details of individual product sales).

The unstructured data may be presented to the computing environment 114in different forms such as a flat file or a conglomerate of datarecords, and may have data values and accompanying time stamps. Thecomputing environment 114 may be used to analyze the unstructured datain a variety of ways to determine the best way to structure (e.g.,hierarchically) that data, such that the structured data is tailored toa type of further analysis that a user wishes to perform on the data.For example, after being processed, the unstructured time stamped datamay be aggregated by time (e.g., into daily time period units) togenerate time series data and/or structured hierarchically according toone or more dimensions (e.g., parameters, attributes, and/or variables).For example, data may be stored in a hierarchical data structure, suchas a ROLAP OR MOLAP database, or may be stored in another tabular form,such as in a flat-hierarchy form.

Data transmission network 100 may also include one or more server farms106. Computing environment 114 may route select communications or datato the one or more sever farms 106 or one or more servers within theserver farms. Server farms 106 can be configured to provide informationin a predetermined manner. For example, server farms 106 may access datato transmit in response to a communication. Server farms 106 may beseparately housed from each other device within data transmissionnetwork 100, such as computing environment 114, and/or may be part of adevice or system.

Server farms 106 may host a variety of different types of dataprocessing as part of data transmission network 100. Server farms 106may receive a variety of different data from network devices, fromcomputing environment 114, from cloud network 116, or from othersources. The data may have been obtained or collected from one or moresensors, as inputs from a control database, or may have been received asinputs from an external system or device. Server farms 106 may assist inprocessing the data by turning raw data into processed data based on oneor more rules implemented by the server farms. For example, sensor datamay be analyzed to determine changes in an environment over time or inreal-time.

Data transmission network 100 may also include one or more cloudnetworks 116. Cloud network 116 may include a cloud infrastructuresystem that provides cloud services. In certain embodiments, servicesprovided by the cloud network 116 may include a host of services thatare made available to users of the cloud infrastructure system ondemand. Cloud network 116 is shown in FIG. 1 as being connected tocomputing environment 114 (and therefore having computing environment114 as its client or user), but cloud network 116 may be connected to orutilized by any of the devices in FIG. 1. Services provided by the cloudnetwork can dynamically scale to meet the needs of its users. The cloudnetwork 116 may comprise one or more computers, servers, and/or systems.In some embodiments, the computers, servers, and/or systems that make upthe cloud network 116 are different from the user's own on-premisescomputers, servers, and/or systems. For example, the cloud network 116may host an application, and a user may, via a communication networksuch as the Internet, on demand, order and use the application.

While each device, server and system in FIG. 1 is shown as a singledevice, it will be appreciated that multiple devices may instead beused. For example, a set of network devices can be used to transmitvarious communications from a single user, or remote server 140 mayinclude a server stack. As another example, data may be processed aspart of computing environment 114.

Each communication within data transmission network 100 (e.g., betweenclient devices, between servers 106 and computing environment 114 orbetween a server and a device) may occur over one or more networks 108.Networks 108 may include one or more of a variety of different types ofnetworks, including a wireless network, a wired network, or acombination of a wired and wireless network. Examples of suitablenetworks include the Internet, a personal area network, a local areanetwork (LAN), a wide area network (WAN), or a wireless local areanetwork (WLAN). A wireless network may include a wireless interface orcombination of wireless interfaces. As an example, a network in the oneor more networks 108 may include a short-range communication channel,such as a Bluetooth or a Bluetooth Low Energy channel. A wired networkmay include a wired interface. The wired and/or wireless networks may beimplemented using routers, access points, bridges, gateways, or thelike, to connect devices in the network 114, as will be furtherdescribed with respect to FIG. 2. The one or more networks 108 can beincorporated entirely within or can include an intranet, an extranet, ora combination thereof. In one embodiment, communications between two ormore systems and/or devices can be achieved by a secure communicationsprotocol, such as secure sockets layer (SSL) or transport layer security(TLS). In addition, data and/or transactional details may be encrypted.

Some aspects may utilize the Internet of Things (IoT), where things(e.g., machines, devices, phones, sensors) can be connected to networksand the data from these things can be collected and processed within thethings and/or external to the things. For example, the IoT can includesensors in many different devices, and high value analytics can beapplied to identify hidden relationships and drive increasedefficiencies. This can apply to both big data analytics and real-time(e.g., ESP) analytics. This will be described further below with respectto FIG. 2.

As noted, computing environment 114 may include a communications grid120 and a transmission network database system 118. Communications grid120 may be a grid-based computing system for processing large amounts ofdata. The transmission network database system 118 may be for managing,storing, and retrieving large amounts of data that are distributed toand stored in the one or more network-attached data stores 110 or otherdata stores that reside at different locations within the transmissionnetwork database system 118. The compute nodes in the grid-basedcomputing system 120 and the transmission network database system 118may share the same processor hardware, such as processors that arelocated within computing environment 114.

FIG. 2 illustrates an example network including an example set ofdevices communicating with each other over an exchange system and via anetwork, according to embodiments of the present technology. As noted,each communication within data transmission network 100 may occur overone or more networks. System 200 includes a network device 204configured to communicate with a variety of types of client devices, forexample client devices 230, over a variety of types of communicationchannels.

As shown in FIG. 2, network device 204 can transmit a communication overa network (e.g., a cellular network via a base station 210). Thecommunication can be routed to another network device, such as networkdevices 205-209, via base station 210. The communication can also berouted to computing environment 214 via base station 210. For example,network device 204 may collect data either from its surroundingenvironment or from other network devices (such as network devices205-209) and transmit that data to computing environment 214.

Although network devices 204-209 are shown in FIG. 2 as a mobile phone,laptop computer, tablet computer, temperature sensor, motion sensor, andaudio sensor respectively, the network devices may be or include sensorsthat are sensitive to detecting aspects of their environment. Forexample, the network devices may include sensors such as water sensors,power sensors, electrical current sensors, chemical sensors, opticalsensors, pressure sensors, geographic or position sensors (e.g., GPS),velocity sensors, acceleration sensors, flow rate sensors, among others.Examples of characteristics that may be sensed include force, torque,load, strain, position, temperature, air pressure, fluid flow, chemicalproperties, resistance, electromagnetic fields, radiation, irradiance,proximity, acoustics, moisture, distance, speed, vibrations,acceleration, electrical potential, electrical current, among others.The sensors may be mounted to various components used as part of avariety of different types of systems (e.g., an oil drilling operation).The network devices may detect and record data related to theenvironment that it monitors, and transmit that data to computingenvironment 214.

As noted, one type of system that may include various sensors thatcollect data to be processed and/or transmitted to a computingenvironment according to certain embodiments includes an oil drillingsystem. For example, the one or more drilling operation sensors mayinclude surface sensors that measure a hook load, a fluid rate, atemperature and a density in and out of the wellbore, a standpipepressure, a surface torque, a rotation speed of a drill pipe, a rate ofpenetration, a mechanical specific energy, etc. and downhole sensorsthat measure a rotation speed of a bit, fluid densities, downholetorque, downhole vibration (axial, tangential, lateral), a weightapplied at a drill bit, an annular pressure, a differential pressure, anazimuth, an inclination, a dog leg severity, a measured depth, avertical depth, a downhole temperature, etc. Besides the raw datacollected directly by the sensors, other data may include parameterseither developed by the sensors or assigned to the system by a client orother controlling device. For example, one or more drilling operationcontrol parameters may control settings such as a mud motor speed toflow ratio, a bit diameter, a predicted formation top, seismic data,weather data, etc. Other data may be generated using physical modelssuch as an earth model, a weather model, a seismic model, a bottom holeassembly model, a well plan model, an annular friction model, etc. Inaddition to sensor and control settings, predicted outputs, of forexample, the rate of penetration, mechanical specific energy, hook load,flow in fluid rate, flow out fluid rate, pump pressure, surface torque,rotation speed of the drill pipe, annular pressure, annular frictionpressure, annular temperature, equivalent circulating density, etc. mayalso be stored in the data warehouse.

In another example, another type of system that may include varioussensors that collect data to be processed and/or transmitted to acomputing environment according to certain embodiments includes a homeautomation or similar automated network in a different environment, suchas an office space, school, public space, sports venue, or a variety ofother locations. Network devices in such an automated network mayinclude network devices that allow a user to access, control, and/orconfigure various home appliances located within the user's home (e.g.,a television, radio, light, fan, humidifier, sensor, microwave, iron,and/or the like), or outside of the user's home (e.g., exterior motionsensors, exterior lighting, garage door openers, sprinkler systems, orthe like). For example, network device 102 may include a home automationswitch that may be coupled with a home appliance. In another embodiment,a network device can allow a user to access, control, and/or configuredevices, such as office-related devices (e.g., copy machine, printer, orfax machine), audio and/or video related devices (e.g., a receiver, aspeaker, a projector, a DVD player, or a television), media-playbackdevices (e.g., a compact disc player, a CD player, or the like),computing devices (e.g., a home computer, a laptop computer, a tablet, apersonal digital assistant (PDA), a computing device, or a wearabledevice), lighting devices (e.g., a lamp or recessed lighting), devicesassociated with a security system, devices associated with an alarmsystem, devices that can be operated in an automobile (e.g., radiodevices, navigation devices), and/or the like. Data may be collectedfrom such various sensors in raw form, or data may be processed by thesensors to create parameters or other data either developed by thesensors based on the raw data or assigned to the system by a client orother controlling device.

In another example, another type of system that may include varioussensors that collect data to be processed and/or transmitted to acomputing environment according to certain embodiments includes a poweror energy grid. A variety of different network devices may be includedin an energy grid, such as various devices within one or more powerplants, energy farms (e.g., wind farm, solar farm, among others) energystorage facilities, factories, homes and businesses of consumers, amongothers. One or more of such devices may include one or more sensors thatdetect energy gain or loss, electrical input or output or loss, and avariety of other efficiencies. These sensors may collect data to informusers of how the energy grid, and individual devices within the grid,may be functioning and how they may be made more efficient.

Network device sensors may also perform processing on data it collectsbefore transmitting the data to the computing environment 114, or beforedeciding whether to transmit data to the computing environment 114. Forexample, network devices may determine whether data collected meetscertain rules, for example by comparing data or values calculated fromthe data and comparing that data to one or more thresholds. The networkdevice may use this data and/or comparisons to determine if the datashould be transmitted to the computing environment 214 for further useor processing.

Computing environment 214 may include machines 220 and 240. Althoughcomputing environment 214 is shown in FIG. 2 as having two machines, 220and 240, computing environment 214 may have only one machine or may havemore than two machines. The machines that make up computing environment214 may include specialized computers, servers, or other machines thatare configured to individually and/or collectively process large amountsof data. The computing environment 214 may also include storage devicesthat include one or more databases of structured data, such as dataorganized in one or more hierarchies, or unstructured data. Thedatabases may communicate with the processing devices within computingenvironment 214 to distribute data to them. Since network devices maytransmit data to computing environment 214, that data may be received bythe computing environment 214 and subsequently stored within thosestorage devices. Data used by computing environment 214 may also bestored in data stores 235, which may also be a part of or connected tocomputing environment 214.

Computing environment 214 can communicate with various devices via oneor more routers 225 or other inter-network or intra-network connectioncomponents. For example, computing environment 214 may communicate withdevices 230 via one or more routers 225. Computing environment 214 maycollect, analyze and/or store data from or pertaining to communications,client device operations, client rules, and/or user-associated actionsstored at one or more data stores 235. Such data may influencecommunication routing to the devices within computing environment 214,how data is stored or processed within computing environment 214, amongother actions.

Notably, various other devices can further be used to influencecommunication routing and/or processing between devices within computingenvironment 214 and with devices outside of computing environment 214.For example, as shown in FIG. 2, computing environment 214 may include aweb server 240. Thus, computing environment 214 can retrieve data ofinterest, such as client information (e.g., product information, clientrules, etc.), technical product details, news, current or predictedweather, and so on.

In addition to computing environment 214 collecting data (e.g., asreceived from network devices, such as sensors, and client devices orother sources) to be processed as part of a big data analytics project,it may also receive data in real time as part of a streaming analyticsenvironment. As noted, data may be collected using a variety of sourcesas communicated via different kinds of networks or locally. Such datamay be received on a real-time streaming basis. For example, networkdevices may receive data periodically from network device sensors as thesensors continuously sense, monitor and track changes in theirenvironments. Devices within computing environment 214 may also performpre-analysis on data it receives to determine if the data receivedshould be processed as part of an ongoing project. The data received andcollected by computing environment 214, no matter what the source ormethod or timing of receipt, may be processed over a period of time fora client to determine results data based on the client's needs andrules.

FIG. 3 illustrates a representation of a conceptual model of acommunications protocol system, according to embodiments of the presenttechnology. More specifically, FIG. 3 identifies operation of acomputing environment in an Open Systems Interaction model thatcorresponds to various connection components. The model 300 shows, forexample, how a computing environment, such as computing environment 314(or computing environment 214 in FIG. 2) may communicate with otherdevices in its network, and control how communications between thecomputing environment and other devices are executed and under whatconditions.

The model can include layers 302-314. The layers are arranged in astack. Each layer in the stack serves the layer one level higher than it(except for the application layer, which is the highest layer), and isserved by the layer one level below it (except for the physical layer,which is the lowest layer). The physical layer is the lowest layerbecause it receives and transmits raw bites of data, and is the farthestlayer from the user in a communications system. On the other hand, theapplication layer is the highest layer because it interacts directlywith a software application.

As noted, the model includes a physical layer 302. Physical layer 302represents physical communication, and can define parameters of thatphysical communication. For example, such physical communication maycome in the form of electrical, optical, or electromagnetic signals.Physical layer 302 also defines protocols that may controlcommunications within a data transmission network.

Link layer 304 defines links and mechanisms used to transmit (i.e.,move) data across a network. The link layer manages node-to-nodecommunications, such as within a grid computing environment. Link layer304 can detect and correct errors (e.g., transmission errors in thephysical layer 302). Link layer 304 can also include a media accesscontrol (MAC) layer and logical link control (LLC) layer.

Network layer 306 defines the protocol for routing within a network. Inother words, the network layer coordinates transferring data acrossnodes in a same network (e.g., such as a grid computing environment).Network layer 306 can also define the processes used to structure localaddressing within the network.

Transport layer 308 can manage the transmission of data and the qualityof the transmission and/or receipt of that data. Transport layer 308 canprovide a protocol for transferring data, such as, for example, aTransmission Control Protocol (TCP). Transport layer 308 can assembleand disassemble data frames for transmission. The transport layer canalso detect transmission errors occurring in the layers below it.

Session layer 310 can establish, maintain, and manage communicationconnections between devices on a network. In other words, the sessionlayer controls the dialogues or nature of communications between networkdevices on the network. The session layer may also establishcheckpointing, adjournment, termination, and restart procedures.

Presentation layer 312 can provide translation for communicationsbetween the application and network layers. In other words, this layermay encrypt, decrypt and/or format data based on data types and/orencodings known to be accepted by an application or network layer.

Application layer 314 interacts directly with software applications andend users, and manages communications between them. Application layer314 can identify destinations, local resource states or availabilityand/or communication content or formatting using the applications.

Intra-network connection components 322 and 324 are shown to operate inlower levels, such as physical layer 302 and link layer 304,respectively. For example, a hub can operate in the physical layer, aswitch can operate in the physical layer, and a router can operate inthe network layer. Inter-network connection components 326 and 328 areshown to operate on higher levels, such as layers 306-314. For example,routers can operate in the network layer and network devices can operatein the transport, session, presentation, and application layers.

As noted, a computing environment 314 can interact with and/or operateon, in various embodiments, one, more, all or any of the various layers.For example, computing environment 314 can interact with a hub (e.g.,via the link layer) so as to adjust which devices the hub communicateswith. The physical layer may be served by the link layer, so it mayimplement such data from the link layer. For example, the computingenvironment 314 may control which devices it will receive data from. Forexample, if the computing environment 314 knows that a certain networkdevice has turned off, broken, or otherwise become unavailable orunreliable, the computing environment 314 may instruct the hub toprevent any data from being transmitted to the computing environment 314from that network device. Such a process may be beneficial to avoidreceiving data that is inaccurate or that has been influenced by anuncontrolled environment. As another example, computing environment 314can communicate with a bridge, switch, router or gateway and influencewhich device within the system (e.g., system 200) the component selectsas a destination. In some embodiments, computing environment 314 caninteract with various layers by exchanging communications with equipmentoperating on a particular layer by routing or modifying existingcommunications. In another embodiment, such as in a grid computingenvironment, a node may determine how data within the environment shouldbe routed (e.g., which node should receive certain data) based oncertain parameters or information provided by other layers within themodel.

As noted, the computing environment 314 may be a part of acommunications grid environment, the communications of which may beimplemented as shown in the protocol of FIG. 3. For example, referringback to FIG. 2, one or more of machines 220 and 240 may be part of acommunications grid computing environment. A gridded computingenvironment may be employed in a distributed system with non-interactiveworkloads where data resides in memory on the machines, or computenodes. In such an environment, analytic code, instead of a databasemanagement system, controls the processing performed by the nodes. Datais co-located by pre-distributing it to the grid nodes, and the analyticcode on each node loads the local data into memory. Each node may beassigned a particular task such as a portion of a processing project, orto organize or control other nodes within the grid.

FIG. 4 illustrates a communications grid computing system 400 includinga variety of control and worker nodes, according to embodiments of thepresent technology. Communications grid computing system 400 includesthree control nodes and one or more worker nodes. Communications gridcomputing system 400 includes control nodes 402, 404, and 406. Thecontrol nodes are communicatively connected via communication paths 451,453, and 455. Therefore, the control nodes may transmit information(e.g., related to the communications grid or notifications), to andreceive information from each other. Although communications gridcomputing system 400 is shown in FIG. 4 as including three controlnodes, the communications grid may include more or less than threecontrol nodes.

Communications grid computing system (or just “communications grid”) 400also includes one or more worker nodes. Shown in FIG. 4 are six workernodes 410-420. Although FIG. 4 shows six worker nodes, a communicationsgrid according to embodiments of the present technology may include moreor less than six worker nodes. The number of worker nodes included in acommunications grid may be dependent upon how large the project or dataset is being processed by the communications grid, the capacity of eachworker node, the time designated for the communications grid to completethe project, among others. Each worker node within the communicationsgrid 400 may be connected (wired or wirelessly, and directly orindirectly) to control nodes 402-406. Therefore, each worker node mayreceive information from the control nodes (e.g., an instruction toperform work on a project) and may transmit information to the controlnodes (e.g., a result from work performed on a project). Furthermore,worker nodes may communicate with each other (either directly orindirectly). For example, worker nodes may transmit data between eachother related to a job being performed or an individual task within ajob being performed by that worker node. However, in certainembodiments, worker nodes may not, for example, be connected(communicatively or otherwise) to certain other worker nodes. In anembodiment, worker nodes may only be able to communicate with thecontrol node that controls it, and may not be able to communicate withother worker nodes in the communications grid, whether they are otherworker nodes controlled by the control node that controls the workernode, or worker nodes that are controlled by other control nodes in thecommunications grid.

A control node may connect with an external device with which thecontrol node may communicate (e.g., a grid user, such as a server orcomputer, may connect to a controller of the grid). For example, aserver or computer may connect to control nodes and may transmit aproject or job to the node. The project may include a data set. The dataset may be of any size. Once the control node receives such a projectincluding a large data set, the control node may distribute the data setor projects related to the data set to be performed by worker nodes.Alternatively, for a project including a large data set, the data setmay be received or stored by a machine other than a control node (e.g.,a Hadoop data node employing Hadoop Distributed File System, or HDFS).

Control nodes may maintain knowledge of the status of the nodes in thegrid (i.e., grid status information), accept work requests from clients,subdivide the work across worker nodes, coordinate the worker nodes,among other responsibilities. Worker nodes may accept work requests froma control node and provide the control node with results of the workperformed by the worker node. A grid may be started from a single node(e.g., a machine, computer, server, etc.). This first node may beassigned or may start as the primary control node that will control anyadditional nodes that enter the grid.

When a project is submitted for execution (e.g., by a client or acontroller of the grid) it may be assigned to a set of nodes. After thenodes are assigned to a project, a data structure (i.e., a communicator)may be created. The communicator may be used by the project forinformation to be shared between the project code running on each node.A communication handle may be created on each node. A handle, forexample, is a reference to the communicator that is valid within asingle process on a single node, and the handle may be used whenrequesting communications between nodes.

A control node, such as control node 402, may be designated as theprimary control node. A server, computer or other external device mayconnect to the primary control node. Once the control node receives aproject, the primary control node may distribute portions of the projectto its worker nodes for execution. For example, when a project isinitiated on communications grid 400, primary control node 402 controlsthe work to be performed for the project in order to complete theproject as requested or instructed. The primary control node maydistribute work to the worker nodes based on various factors, such aswhich subsets or portions of projects may be completed most efficientlyand in the correct amount of time. For example, a worker node mayperform analysis on a portion of data that is already local (e.g.,stored on) the worker node. The primary control node also coordinatesand processes the results of the work performed by each worker nodeafter each worker node executes and completes its job. For example, theprimary control node may receive a result from one or more worker nodes,and the control node may organize (e.g., collect and assemble) theresults received and compile them to produce a complete result for theproject received from the end user.

Any remaining control nodes, such as control nodes 404 and 406, may beassigned as backup control nodes for the project. In an embodiment,backup control nodes may not control any portion of the project.Instead, backup control nodes may serve as a backup for the primarycontrol node and take over as primary control node if the primarycontrol node were to fail. If a communications grid were to include onlya single control node, and the control node were to fail (e.g., thecontrol node is shut off or breaks) then the communications grid as awhole may fail and any project or job being run on the communicationsgrid may fail and may not complete. While the project may be run again,such a failure may cause a delay (severe delay in some cases, such asovernight delay) in completion of the project. Therefore, a grid withmultiple control nodes, including a backup control node, may bebeneficial.

To add another node or machine to the grid, the primary control node mayopen a pair of listening sockets, for example. A socket may be used toaccept work requests from clients, and the second socket may be used toaccept connections from other grid nodes. The primary control node maybe provided with a list of other nodes (e.g., other machines, computers,servers) that will participate in the grid, and the role that each nodewill fill in the grid. Upon startup of the primary control node (e.g.,the first node on the grid), the primary control node may use a networkprotocol to start the server process on every other node in the grid.Command line parameters, for example, may inform each node of one ormore pieces of information, such as: the role that the node will have inthe grid, the host name of the primary control node, the port number onwhich the primary control node is accepting connections from peer nodes,among others. The information may also be provided in a configurationfile, transmitted over a secure shell tunnel, recovered from aconfiguration server, among others. While the other machines in the gridmay not initially know about the configuration of the grid, thatinformation may also be sent to each other node by the primary controlnode. Updates of the grid information may also be subsequently sent tothose nodes.

For any control node other than the primary control node added to thegrid, the control node may open three sockets. The first socket mayaccept work requests from clients, the second socket may acceptconnections from other grid members, and the third socket may connect(e.g., permanently) to the primary control node. When a control node(e.g., primary control node) receives a connection from another controlnode, it first checks to see if the peer node is in the list ofconfigured nodes in the grid. If it is not on the list, the control nodemay clear the connection. If it is on the list, it may then attempt toauthenticate the connection. If authentication is successful, theauthenticating node may transmit information to its peer, such as theport number on which a node is listening for connections, the host nameof the node, information about how to authenticate the node, among otherinformation. When a node, such as the new control node, receivesinformation about another active node, it will check to see if italready has a connection to that other node. If it does not have aconnection to that node, it may then establish a connection to thatcontrol node.

Any worker node added to the grid may establish a connection to theprimary control node and any other control nodes on the grid. Afterestablishing the connection, it may authenticate itself to the grid(e.g., any control nodes, including both primary and backup, or a serveror user controlling the grid). After successful authentication, theworker node may accept configuration information from the control node.

When a node joins a communications grid (e.g., when the node is poweredon or connected to an existing node on the grid or both), the node isassigned (e.g., by an operating system of the grid) a universally uniqueidentifier (UUID). This unique identifier may help other nodes andexternal entities (devices, users, etc.) to identify the node anddistinguish it from other nodes. When a node is connected to the grid,the node may share its unique identifier with the other nodes in thegrid. Since each node may share its unique identifier, each node mayknow the unique identifier of every other node on the grid. Uniqueidentifiers may also designate a hierarchy of each of the nodes (e.g.,backup control nodes) within the grid. For example, the uniqueidentifiers of each of the backup control nodes may be stored in a listof backup control nodes to indicate an order in which the backup controlnodes will take over for a failed primary control node to become a newprimary control node. However, a hierarchy of nodes may also bedetermined using methods other than using the unique identifiers of thenodes. For example, the hierarchy may be predetermined, or may beassigned based on other predetermined factors.

The grid may add new machines at any time (e.g., initiated from anycontrol node). Upon adding a new node to the grid, the control node mayfirst add the new node to its table of grid nodes. The control node mayalso then notify every other control node about the new node. The nodesreceiving the notification may acknowledge that they have updated theirconfiguration information.

Primary control node 402 may, for example, transmit one or morecommunications to backup control nodes 404 and 406 (and, for example, toother control or worker nodes within the communications grid). Suchcommunications may sent periodically, at fixed time intervals, betweenknown fixed stages of the project's execution, among other protocols.The communications transmitted by primary control node 402 may be ofvaried types and may include a variety of types of information. Forexample, primary control node 402 may transmit snapshots (e.g., statusinformation) of the communications grid so that backup control node 404always has a recent snapshot of the communications grid. The snapshot orgrid status may include, for example, the structure of the grid(including, for example, the worker nodes in the grid, uniqueidentifiers of the nodes, or their relationships with the primarycontrol node) and the status of a project (including, for example, thestatus of each worker node's portion of the project). The snapshot mayalso include analysis or results received from worker nodes in thecommunications grid. The backup control nodes may receive and store thebackup data received from the primary control node. The backup controlnodes may transmit a request for such a snapshot (or other information)from the primary control node, or the primary control node may send suchinformation periodically to the backup control nodes.

As noted, the backup data may allow the backup control node to take overas primary control node if the primary control node fails withoutrequiring the grid to start the project over from scratch. If theprimary control node fails, the backup control node that will take overas primary control node may retrieve the most recent version of thesnapshot received from the primary control node and use the snapshot tocontinue the project from the stage of the project indicated by thebackup data. This may prevent failure of the project as a whole.

A backup control node may use various methods to determine that theprimary control node has failed. In one example of such a method, theprimary control node may transmit (e.g., periodically) a communicationto the backup control node that indicates that the primary control nodeis working and has not failed, such as a heartbeat communication. Thebackup control node may determine that the primary control node hasfailed if the backup control node has not received a heartbeatcommunication for a certain predetermined period of time. Alternatively,a backup control node may also receive a communication from the primarycontrol node itself (before it failed) or from a worker node that theprimary control node has failed, for example because the primary controlnode has failed to communicate with the worker node.

Different methods may be performed to determine which backup controlnode of a set of backup control nodes (e.g., backup control nodes 404and 406) will take over for failed primary control node 402 and becomethe new primary control node. For example, the new primary control nodemay be chosen based on a ranking or “hierarchy” of backup control nodesbased on their unique identifiers. In an alternative embodiment, abackup control node may be assigned to be the new primary control nodeby another device in the communications grid or from an external device(e.g., a system infrastructure or an end user, such as a server orcomputer, controlling the communications grid). In another alternativeembodiment, the backup control node that takes over as the new primarycontrol node may be designated based on bandwidth or other statisticsabout the communications grid.

A worker node within the communications grid may also fail. If a workernode fails, work being performed by the failed worker node may beredistributed amongst the operational worker nodes. In an alternativeembodiment, the primary control node may transmit a communication toeach of the operable worker nodes still on the communications grid thateach of the worker nodes should purposefully fail also. After each ofthe worker nodes fail, they may each retrieve their most recent savedcheckpoint of their status and re-start the project from that checkpointto minimize lost progress on the project being executed.

FIG. 5 illustrates a flow chart showing an example process for adjustinga communications grid or a work project in a communications grid after afailure of a node, according to embodiments of the present technology.The process may include, for example, receiving grid status informationincluding a project status of a portion of a project being executed by anode in the communications grid, as described in operation 502. Forexample, a control node (e.g., a backup control node connected to aprimary control node and a worker node on a communications grid) mayreceive grid status information, where the grid status informationincludes a project status of the primary control node or a projectstatus of the worker node. The project status of the primary controlnode and the project status of the worker node may include a status ofone or more portions of a project being executed by the primary andworker nodes in the communications grid. The process may also includestoring the grid status information, as described in operation 504. Forexample, a control node (e.g., a backup control node) may store thereceived grid status information locally within the control node.Alternatively, the grid status information may be sent to another devicefor storage where the control node may have access to the information.

The process may also include receiving a failure communicationcorresponding to a node in the communications grid in operation 506. Forexample, a node may receive a failure communication including anindication that the primary control node has failed, prompting a backupcontrol node to take over for the primary control node. In analternative embodiment, a node may receive a failure that a worker nodehas failed, prompting a control node to reassign the work beingperformed by the worker node. The process may also include reassigning anode or a portion of the project being executed by the failed node, asdescribed in operation 508. For example, a control node may designatethe backup control node as a new primary control node based on thefailure communication upon receiving the failure communication. If thefailed node is a worker node, a control node may identify a projectstatus of the failed worker node using the snapshot of thecommunications grid, where the project status of the failed worker nodeincludes a status of a portion of the project being executed by thefailed worker node at the failure time.

The process may also include receiving updated grid status informationbased on the reassignment, as described in operation 510, andtransmitting a set of instructions based on the updated grid statusinformation to one or more nodes in the communications grid, asdescribed in operation 512. The updated grid status information mayinclude an updated project status of the primary control node or anupdated project status of the worker node. The updated information maybe transmitted to the other nodes in the grid to update their stalestored information.

FIG. 6 illustrates a portion of a communications grid computing system600 including a control node and a worker node, according to embodimentsof the present technology. Communications grid 600 computing systemincludes one control node (control node 602) and one worker node (workernode 610) for purposes of illustration, but may include more workerand/or control nodes. The control node 602 is communicatively connectedto worker node 610 via communication path 650. Therefore, control node602 may transmit information (e.g., related to the communications gridor notifications), to and receive information from worker node 610 viapath 650.

Similar to in FIG. 4, communications grid computing system (or just“communications grid”) 600 includes data processing nodes (control node602 and worker node 610). Nodes 602 and 610 comprise multi-core dataprocessors. Each node 602 and 610 includes a grid-enabled softwarecomponent (GESC) 620 that executes on the data processor associated withthat node and interfaces with buffer memory 622 also associated withthat node. Each node 602 and 610 includes a database management software(DBMS) 628 that executes on a database server (not shown) at controlnode 602 and on a database server (not shown) at worker node 610.

Each node also includes a data store 624. Data stores 624, similar tonetwork-attached data stores 110 in FIG. 1 and data stores 235 in FIG.2, are used to store data to be processed by the nodes in the computingenvironment. Data stores 624 may also store any intermediate or finaldata generated by the computing system after being processed, forexample in non-volatile memory. However in certain embodiments, theconfiguration of the grid computing environment allows its operations tobe performed such that intermediate and final data results can be storedsolely in volatile memory (e.g., RAM), without a requirement thatintermediate or final data results be stored to non-volatile types ofmemory. Storing such data in volatile memory may be useful in certainsituations, such as when the grid receives queries (e.g., ad hoc) from aclient and when responses, which are generated by processing largeamounts of data, need to be generated quickly or on-the-fly. In such asituation, the grid may be configured to retain the data within memoryso that responses can be generated at different levels of detail and sothat a client may interactively query against this information.

Each node also includes a user-defined function (UDF) 626. The UDFprovides a mechanism for the DMBS 628 to transfer data to or receivedata from the database stored in the data stores 624 that are managed bythe DBMS. For example, UDF 626 can be invoked by the DBMS to providedata to the GESC for processing. The UDF 626 may establish a socketconnection (not shown) with the GESC to transfer the data.Alternatively, the UDF 626 can transfer data to the GESC by writing datato shared memory accessible by both the UDF and the GESC.

The GESC 620 at the nodes 602 and 620 may be connected via a network,such as network 108 shown in FIG. 1. Therefore, nodes 602 and 620 cancommunicate with each other via the network using a predeterminedcommunication protocol such as, for example, the Message PassingInterface (MPI). Each GESC 620 can engage in point-to-pointcommunication with the GESC at another node or in collectivecommunication with multiple GESCs via the network. The GESC 620 at eachnode may contain identical (or nearly identical) software instructions.Each node may be capable of operating as either a control node or aworker node. The GESC at the control node 602 can communicate, over acommunication path 652, with a client deice 630. More specifically,control node 602 may communicate with client application 632 hosted bythe client device 630 to receive queries and to respond to those queriesafter processing large amounts of data.

DMBS 628 may control the creation, maintenance, and use of database ordata structure (not shown) within a nodes 602 or 610. The database mayorganize data stored in data stores 624. The DMBS 628 at control node602 may accept requests for data and transfer the appropriate data forthe request. With such a process, collections of data may be distributedacross multiple physical locations. In this example, each node 602 and610 stores a portion of the total data managed by the management systemin its associated data store 624.

Furthermore, the DBMS may be responsible for protecting against dataloss using replication techniques. Replication includes providing abackup copy of data stored on one node on one or more other nodes.Therefore, if one node fails, the data from the failed node can berecovered from a replicated copy residing at another node. However, asdescribed herein with respect to FIG. 4, data or status information foreach node in the communications grid may also be shared with each nodeon the grid.

FIG. 7 illustrates a flow chart showing an example method for executinga project within a grid computing system, according to embodiments ofthe present technology. As described with respect to FIG. 6, the GESC atthe control node may transmit data with a client device (e.g., clientdevice 630) to receive queries for executing a project and to respond tothose queries after large amounts of data have been processed. The querymay be transmitted to the control node, where the query may include arequest for executing a project, as described in operation 702. Thequery can contain instructions on the type of data analysis to beperformed in the project and whether the project should be executedusing the grid-based computing environment, as shown in operation 704.

To initiate the project, the control node may determine if the queryrequests use of the grid-based computing environment to execute theproject. If the determination is no, then the control node initiatesexecution of the project in a solo environment (e.g., at the controlnode), as described in operation 710. If the determination is yes, thecontrol node may initiate execution of the project in the grid-basedcomputing environment, as described in operation 706. In such asituation, the request may include a requested configuration of thegrid. For example, the request may include a number of control nodes anda number of worker nodes to be used in the grid when executing theproject. After the project has been completed, the control node maytransmit results of the analysis yielded by the grid, as described inoperation 708. Whether the project is executed in a solo or grid-basedenvironment, the control node provides the results of the project.

As noted with respect to FIG. 2, the computing environments describedherein may collect data (e.g., as received from network devices, such assensors, such as network devices 204-209 in FIG. 2, and client devicesor other sources) to be processed as part of a data analytics project,and data may be received in real time as part of a streaming analyticsenvironment (e.g., ESP). Data may be collected using a variety ofsources as communicated via different kinds of networks or locally, suchas on a real-time streaming basis. For example, network devices mayreceive data periodically from network device sensors as the sensorscontinuously sense, monitor and track changes in their environments.More specifically, an increasing number of distributed applicationsdevelop or produce continuously flowing data from distributed sources byapplying queries to the data before distributing the data togeographically distributed recipients. An event stream processing engine(ESPE) may continuously apply the queries to the data as it is receivedand determines which entities should receive the data. Client or otherdevices may also subscribe to the ESPE or other devices processing ESPdata so that they can receive data after processing, based on forexample the entities determined by the processing engine. For example,client devices 230 in FIG. 2 may subscribe to the ESPE in computingenvironment 214. In another example, event subscription devices 874 a-c,described further with respect to FIG. 10, may also subscribe to theESPE. The ESPE may determine or define how input data or event streamsfrom network devices or other publishers (e.g., network devices 204-209in FIG. 2) are transformed into meaningful output data to be consumed bysubscribers, such as for example client devices 230 in FIG. 2.

FIG. 8 illustrates a block diagram including components of an EventStream Processing Engine (ESPE), according to embodiments of the presenttechnology. ESPE 800 may include one or more projects 802. A project maybe described as a second-level container in an engine model managed byESPE 800 where a thread pool size for the project may be defined by auser. Each project of the one or more projects 802 may include one ormore continuous queries 804 that contain data flows, which are datatransformations of incoming event streams. The one or more continuousqueries 804 may include one or more source windows 806 and one or morederived windows 808.

The ESPE may receive streaming data over a period of time related tocertain events, such as events or other data sensed by one or morenetwork devices. The ESPE may perform operations associated withprocessing data created by the one or more devices. For example, theESPE may receive data from the one or more network devices 204-209 shownin FIG. 2. As noted, the network devices may include sensors that sensedifferent aspects of their environments, and may collect data over timebased on those sensed observations. For example, the ESPE may beimplemented within one or more of machines 220 and 240 shown in FIG. 2.The ESPE may be implemented within such a machine by an ESP application.An ESP application may embed an ESPE with its own dedicated thread poolor pools into its application space where the main application threadcan do application-specific work and the ESPE processes event streams atleast by creating an instance of a model into processing objects.

The engine container is the top-level container in a model that managesthe resources of the one or more projects 802. In an illustrativeembodiment, for example, there may be only one ESPE 800 for eachinstance of the ESP application, and ESPE 800 may have a unique enginename. Additionally, the one or more projects 802 may each have uniqueproject names, and each query may have a unique continuous query nameand begin with a uniquely named source window of the one or more sourcewindows 806. ESPE 800 may or may not be persistent.

Continuous query modeling involves defining directed graphs of windowsfor event stream manipulation and transformation. A window in thecontext of event stream manipulation and transformation is a processingnode in an event stream processing model. A window in a continuous querycan perform aggregations, computations, pattern-matching, and otheroperations on data flowing through the window. A continuous query may bedescribed as a directed graph of source, relational, pattern matching,and procedural windows. The one or more source windows 806 and the oneor more derived windows 808 represent continuously executing queriesthat generate updates to a query result set as new event blocks streamthrough ESPE 800. A directed graph, for example, is a set of nodesconnected by edges, where the edges have a direction associated withthem.

An event object may be described as a packet of data accessible as acollection of fields, with at least one of the fields defined as a keyor unique identifier (ID). The event object may be created using avariety of formats including binary, alphanumeric, XML, etc. Each eventobject may include one or more fields designated as a primary identifier(ID) for the event so ESPE 800 can support operation codes (opcodes) forevents including insert, update, upsert, and delete. Upsert opcodesupdate the event if the key field already exists; otherwise, the eventis inserted. For illustration, an event object may be a packed binaryrepresentation of a set of field values and include both metadata andfield data associated with an event. The metadata may include an opcodeindicating if the event represents an insert, update, delete, or upsert,a set of flags indicating if the event is a normal, partial-update, or aretention generated event from retention policy management, and a set ofmicrosecond timestamps that can be used for latency measurements.

An event block object may be described as a grouping or package of eventobjects. An event stream may be described as a flow of event blockobjects. A continuous query of the one or more continuous queries 804transforms a source event stream made up of streaming event blockobjects published into ESPE 800 into one or more output event streamsusing the one or more source windows 806 and the one or more derivedwindows 808. A continuous query can also be thought of as data flowmodeling.

The one or more source windows 806 are at the top of the directed graphand have no windows feeding into them. Event streams are published intothe one or more source windows 806, and from there, the event streamsmay be directed to the next set of connected windows as defined by thedirected graph. The one or more derived windows 808 are all instantiatedwindows that are not source windows and that have other windowsstreaming events into them. The one or more derived windows 808 mayperform computations or transformations on the incoming event streams.The one or more derived windows 808 transform event streams based on thewindow type (that is operators such as join, filter, compute, aggregate,copy, pattern match, procedural, union, etc.) and window settings. Asevent streams are published into ESPE 800, they are continuouslyqueried, and the resulting sets of derived windows in these queries arecontinuously updated.

FIG. 9 illustrates a flow chart showing an example process includingoperations performed by an event stream processing engine, according tosome embodiments of the present technology. As noted, the ESPE 800 (oran associated ESP application) defines how input event streams aretransformed into meaningful output event streams. More specifically, theESP application may define how input event streams from publishers(e.g., network devices providing sensed data) are transformed intomeaningful output event streams consumed by subscribers (e.g., a dataanalytics project being executed by a machine or set of machines).

Within the application, a user may interact with one or more userinterface windows presented to the user in a display under control ofthe ESPE independently or through a browser application in an orderselectable by the user. For example, a user may execute an ESPapplication, which causes presentation of a first user interface window,which may include a plurality of menus and selectors such as drop downmenus, buttons, text boxes, hyperlinks, etc. associated with the ESPapplication as understood by a person of skill in the art. As furtherunderstood by a person of skill in the art, various operations may beperformed in parallel, for example, using a plurality of threads.

At operation 900, an ESP application may define and start an ESPE,thereby instantiating an ESPE at a device, such as machine 220 and/or240. In an operation 902, the engine container is created. Forillustration, ESPE 800 may be instantiated using a function call thatspecifies the engine container as a manager for the model.

In an operation 904, the one or more continuous queries 804 areinstantiated by ESPE 800 as a model. The one or more continuous queries804 may be instantiated with a dedicated thread pool or pools thatgenerate updates as new events stream through ESPE 800. Forillustration, the one or more continuous queries 804 may be created tomodel business processing logic within ESPE 800, to predict eventswithin ESPE 800, to model a physical system within ESPE 800, to predictthe physical system state within ESPE 800, etc. For example, as noted,ESPE 800 may be used to support sensor data monitoring and management(e.g., sensing may include force, torque, load, strain, position,temperature, air pressure, fluid flow, chemical properties, resistance,electromagnetic fields, radiation, irradiance, proximity, acoustics,moisture, distance, speed, vibrations, acceleration, electricalpotential, or electrical current, etc.).

ESPE 800 may analyze and process events in motion or “event streams.”Instead of storing data and running queries against the stored data,ESPE 800 may store queries and stream data through them to allowcontinuous analysis of data as it is received. The one or more sourcewindows 806 and the one or more derived windows 808 may be created basedon the relational, pattern matching, and procedural algorithms thattransform the input event streams into the output event streams tomodel, simulate, score, test, predict, etc. based on the continuousquery model defined and application to the streamed data.

In an operation 906, a publish/subscribe (pub/sub) capability isinitialized for ESPE 800. In an illustrative embodiment, a pub/subcapability is initialized for each project of the one or more projects802. To initialize and enable pub/sub capability for ESPE 800, a portnumber may be provided. Pub/sub clients can use a host name of an ESPdevice running the ESPE and the port number to establish pub/subconnections to ESPE 800.

FIG. 10 illustrates an ESP system 850 interfacing between publishingdevice 872 and event subscribing devices 874 a-c, according toembodiments of the present technology. ESP system 850 may include ESPdevice or subsystem 851, event publishing device 872, an eventsubscribing device A 874 a, an event subscribing device B 874 b, and anevent subscribing device C 874 c. Input event streams are output to ESPdevice 851 by publishing device 872. In alternative embodiments, theinput event streams may be created by a plurality of publishing devices.The plurality of publishing devices further may publish event streams toother ESP devices. The one or more continuous queries instantiated byESPE 800 may analyze and process the input event streams to form outputevent streams output to event subscribing device A 874 a, eventsubscribing device B 874 b, and event subscribing device C 874 c. ESPsystem 850 may include a greater or a fewer number of event subscribingdevices of event subscribing devices.

Publish-subscribe is a message-oriented interaction paradigm based onindirect addressing. Processed data recipients specify their interest inreceiving information from ESPE 800 by subscribing to specific classesof events, while information sources publish events to ESPE 800 withoutdirectly addressing the receiving parties. ESPE 800 coordinates theinteractions and processes the data. In some cases, the data sourcereceives confirmation that the published information has been receivedby a data recipient.

A publish/subscribe API may be described as a library that enables anevent publisher, such as publishing device 872, to publish event streamsinto ESPE 800 or an event subscriber, such as event subscribing device A874 a, event subscribing device B 874 b, and event subscribing device C874 c, to subscribe to event streams from ESPE 800. For illustration,one or more publish/subscribe APIs may be defined. Using thepublish/subscribe API, an event publishing application may publish eventstreams into a running event stream processor project source window ofESPE 800, and the event subscription application may subscribe to anevent stream processor project source window of ESPE 800.

The publish/subscribe API provides cross-platform connectivity andendianness compatibility between ESP application and other networkedapplications, such as event publishing applications instantiated atpublishing device 872, and event subscription applications instantiatedat one or more of event subscribing device A 874 a, event subscribingdevice B 874 b, and event subscribing device C 874 c.

Referring back to FIG. 9, operation 906 initializes thepublish/subscribe capability of ESPE 800. In an operation 908, the oneor more projects 802 are started. The one or more started projects mayrun in the background on an ESP device. In an operation 910, an eventblock object is received from one or more computing device of the eventpublishing device 872.

ESP subsystem 800 may include a publishing client 852, ESPE 800, asubscribing client A 854, a subscribing client B 856, and a subscribingclient C 858. Publishing client 852 may be started by an eventpublishing application executing at publishing device 872 using thepublish/subscribe API. Subscribing client A 854 may be started by anevent subscription application A, executing at event subscribing deviceA 874 a using the publish/subscribe API. Subscribing client B 856 may bestarted by an event subscription application B executing at eventsubscribing device B 874 b using the publish/subscribe API. Subscribingclient C 858 may be started by an event subscription application Cexecuting at event subscribing device C 874 c using thepublish/subscribe API.

An event block object containing one or more event objects is injectedinto a source window of the one or more source windows 806 from aninstance of an event publishing application on event publishing device872. The event block object may generated, for example, by the eventpublishing application and may be received by publishing client 852. Aunique ID may be maintained as the event block object is passed betweenthe one or more source windows 806 and/or the one or more derivedwindows 808 of ESPE 800, and to subscribing client A 854, subscribingclient B 806, and subscribing client C 808 and to event subscriptiondevice A 874 a, event subscription device B 874 b, and eventsubscription device C 874 c. Publishing client 852 may further generateand include a unique embedded transaction ID in the event block objectas the event block object is processed by a continuous query, as well asthe unique ID that publishing device 872 assigned to the event blockobject.

In an operation 912, the event block object is processed through the oneor more continuous queries 804. In an operation 914, the processed eventblock object is output to one or more computing devices of the eventsubscribing devices 874 a-c. For example, subscribing client A 804,subscribing client B 806, and subscribing client C 808 may send thereceived event block object to event subscription device A 874 a, eventsubscription device B 874 b, and event subscription device C 874 c,respectively.

ESPE 800 maintains the event block containership aspect of the receivedevent blocks from when the event block is published into a source windowand works its way through the directed graph defined by the one or morecontinuous queries 804 with the various event translations before beingoutput to subscribers. Subscribers can correlate a group of subscribedevents back to a group of published events by comparing the unique ID ofthe event block object that a publisher, such as publishing device 872,attached to the event block object with the event block ID received bythe subscriber.

In an operation 916, a determination is made concerning whether or notprocessing is stopped. If processing is not stopped, processingcontinues in operation 910 to continue receiving the one or more eventstreams containing event block objects from the, for example, one ormore network devices. If processing is stopped, processing continues inan operation 918. In operation 918, the started projects are stopped. Inoperation 920, the ESPE is shutdown.

As noted, in some embodiments, big data is processed for an analyticsproject after the data is received and stored. In other embodiments,distributed applications process continuously flowing data in real-timefrom distributed sources by applying queries to the data beforedistributing the data to geographically distributed recipients. Asnoted, an event stream processing engine (ESPE) may continuously applythe queries to the data as it is received and determines which entitiesreceive the processed data. This allows for large amounts of data beingreceived and/or collected in a variety of environments to be processedand distributed in real time. For example, as shown with respect to FIG.2, data may be collected from network devices that may include deviceswithin the internet of things, such as devices within a home automationnetwork. However, such data may be collected from a variety of differentresources in a variety of different environments. In any such situation,embodiments of the present technology allow for real-time processing ofsuch data.

Aspects of the current disclosure provide technical solutions totechnical problems, such as computing problems that arise when an ESPdevice fails which results in a complete service interruption andpotentially significant data loss. The data loss can be catastrophicwhen the streamed data is supporting mission critical operations such asthose in support of an ongoing manufacturing or drilling operation. Anembodiment of an ESP system achieves a rapid and seamless failover ofESPE running at the plurality of ESP devices without serviceinterruption or data loss, thus significantly improving the reliabilityof an operational system that relies on the live or real-time processingof the data streams. The event publishing systems, the event subscribingsystems, and each ESPE not executing at a failed ESP device are notaware of or effected by the failed ESP device. The ESP system mayinclude thousands of event publishing systems and event subscribingsystems. The ESP system keeps the failover logic and awareness withinthe boundaries of out-messaging network connector and out-messagingnetwork device.

In one example embodiment, a system is provided to support a failoverwhen event stream processing (ESP) event blocks. The system includes,but is not limited to, an out-messaging network device and a computingdevice. The computing device includes, but is not limited to, aprocessor and a computer-readable medium operably coupled to theprocessor. The processor is configured to execute an ESP engine (ESPE).The computer-readable medium has instructions stored thereon that, whenexecuted by the processor, cause the computing device to support thefailover. An event block object is received from the ESPE that includesa unique identifier. A first status of the computing device as active orstandby is determined. When the first status is active, a second statusof the computing device as newly active or not newly active isdetermined. Newly active is determined when the computing device isswitched from a standby status to an active status. When the secondstatus is newly active, a last published event block object identifierthat uniquely identifies a last published event block object isdetermined. A next event block object is selected from a non-transitorycomputer-readable medium accessible by the computing device. The nextevent block object has an event block object identifier that is greaterthan the determined last published event block object identifier. Theselected next event block object is published to an out-messagingnetwork device. When the second status of the computing device is notnewly active, the received event block object is published to theout-messaging network device. When the first status of the computingdevice is standby, the received event block object is stored in thenon-transitory computer-readable medium.

FIG. 11A illustrates a block diagram of an example embodiment of adistributed processing system 1000 incorporating one or more storagedevices 1100, multiple node devices 1700, and a control device 1500. Asdepicted, these devices 1100, 1500 and/or 1700 may exchangecommunications thereamong related to the storage and retrieval of a dataset 1330 via a network 1999, including one or more of metadata 1335,data set portions 1732, node data 1530 and/or pointer data 1735.However, one or more of the devices 1100, 1500 and/or 1700 may exchangeother data entirely unrelated to the storage and retrieval of the dataset 1330 with each other and/or with still other devices (not shown) viathe network 1999. In various embodiments, the network 1999 may be asingle network that may extend within a single building or otherrelatively limited area, a combination of connected networks that mayextend a considerable distance, and/or may include the Internet. Thus,the network 1999 may be based on any of a variety (or combination) ofcommunications technologies by which communications may be effected,including without limitation, wired technologies employing electricallyand/or optically conductive cabling, and wireless technologies employinginfrared, radio frequency (RF) or other forms of wireless transmission.

The data set 1330 may be divisible into the data set portions 1732.Different ones of the data set portions 1732 may be temporarily storedby different ones of the node devices 1700 as the multiple node devices1700 separately, and at least partially in parallel, perform processingtasks with the data set portions 1732. Such at least partially parallelperformances of processing tasks by the multiple node devices 1700 maybe coordinated by the control device 1500. The control device 1500 maydistribute indications of the processing tasks to be performed and/orother related information, such as the metadata 1335, among the multiplenode devices 1700. The control device 1500 may also receive indicationsof progress in the separate, but at least partially parallel,performance of processing tasks from each of the node devices 1700.

In preparation for and/or in support of such processing tasks, the dataset 1330 may be stored for longer term storage as a single data file1110 by the one or more storage devices 1100. Where the data set 1330 isemployed by the multiple node devices 1700 as an input to suchprocessing tasks, the multiple node devices 1700 may retrievecorresponding ones of the data set portions 1732, at least partially inparallel, from the one or more storage devices 1100. Alternatively oradditionally, where the data set 1330 is generated as an output of suchprocessing tasks, the multiple node devices 1700 may store correspondingones of the data set portions 1732, at least partially in parallel, tothe one or more storage devices 1100. Such at least partially parallelexchanges of the data set 1330 between the multiple node devices 1700and the one or more storage devices 1100 may also be coordinated by thecontrol device 1500. The control device 1500 may distribute, to eachnode device 1700, one or more pointers to locations within the data file1110 at which one or more corresponding data set portions 1732 may bestored, and/or from which one or more corresponding data set portions1732 may be retrieved.

In various embodiments, each of the one or more storage devices 1100 mayincorporate one or more of a processor component 1150, a storage 1160and a network interface 1190 to couple each of the one or more storagedevices 1100 to the network 1999. The storage 1160 may store a controlroutine 1140 and/or at least a portion of the data file 1110 in whichthe data set 1330 is stored. The control routine 1140 may incorporate asequence of instructions operative on the processor component 1150 toimplement logic to perform various functions. In executing the controlroutine 1140, the processor component 1150 of each of the one or morestorage devices 1100 may operate the network interface 1190 to receivethe data set portions 1732 from corresponding ones of the node devices1700, and may store the received data set portions 1732 within the datafile 1110. Alternatively or additionally, the processor component 1150may retrieve the data set portions 1732 from the data file 1110, and mayoperate the network interface 1190 to transmit the retrieved data setportions 1732 to corresponding ones of the node devices 1700.

In various embodiments, each of the multiple node devices 1700 mayincorporate one or more of a processor component 1750, a storage 1760and a network interface 1790 to couple each of the node devices 1700 tothe network 1999. The storage 1760 may store a control routine 1740, themetadata 1335, one or more of the data set portions 1732, and/or thepointer data 1735. The control routine 1740 may incorporate a sequenceof instructions operative on the processor component 1750 to implementlogic to perform various functions. In executing the control routine1740, the processor component 1750 of each of the node devices 1700 mayoperate the network interface 1790 to receive indications of processingtasks to perform on one or more of the data set portions 1732 atpartially in parallel with others of the multiple node devices 1700,and/or other related information, from the control device 1500.Alternatively or additionally, the processor component 1750 may operatethe network interface 1790 to transmit one or more of the data setportions 1732 to the one or more storage devices 1100, and/or to receiveone or more of the data set portions 1732 from the one or more storagedevices 1100 in support of performing such processing tasks.

In various embodiments, the control device 1500 may incorporate one ormore of a processor component 1550, a storage 1560 and a networkinterface 1590 to couple the control device 1500 to the network 1999.The storage 1560 may store a control routine 1540, the metadata 1335,map data 1510 and/or node data 1530. The control routine 1540 mayincorporate a sequence of instructions operative on the processorcomponent 1550 to implement logic to perform various functions. Inexecuting the control routine 1540, the processor component 1550 of thecontrol device 1500 may operate the network interface 1590 to transmitindications to each of the node devices 1700 of processing tasks toperform on one or more of the data set portions 1732 at partially inparallel with others of the multiple node devices 1700, and/or otherrelated information. Alternatively or additionally, the processorcomponent 1550 may operate the network interface 1590 to exchange one ormore of the metadata 1335 and the map data 1510 with at least one of theone or more storage devices 1100.

FIG. 11B illustrates a block diagram of an alternate example embodimentof the distributed processing system 1000 that is substantially similarto the example of FIG. 11A, but featuring an alternate embodiment of oneof the node devices 1700 that additionally performs the coordinatingfunctions of the control device 1500 in lieu of there being a separateand distinct control device 1500. As depicted, in some embodiments, suchan alternate embodiment of the node device 1700 may additionallyincorporate a controller 1507 that, itself, incorporates the processorcomponent 1550 and the storage 1560 that were depicted as components ofthe separate control device 1500 of FIG. 11A to perform the coordinatingfunctions. As also depicted as an alternative, in some embodiments, theprocessor component 1750 of such an alternate embodiment of the nodedevice 1700 may be caused by its execution of a virtual machine manager(VMM) routine 1745 stored within the storage 1760 to generate a virtualmachines VMs 1565 and/or 1765. Within the VM 1765, the processorcomponent 1750 may execute the control routine 1740 to performprocessing tasks with one or more data set portions 1732 at leastpartially in parallel with others of the node devices 1700.Alternatively or additionally, within the VM 1565, the processorcomponent 1750 may execute the control routine 1540 to perform suchcoordinating tasks as have been described as being otherwise performedby the processor component 1550 of the control device 1500 of FIG. 11Aand/or by the controller 1507.

FIGS. 12A, 12B and 12C, together, illustrate an example of the manner inwhich the data set 1330 may be stored within the data file 1110 by theone or more storage devices 1100. The data of the data set 1330 may beany of a variety of types of data (e.g., societal statistics data,business operations data, raw data from an experiment, financial data,medical treatment analysis data, etc.), and may be organized within thedata set 1330 in any of a variety of ways (e.g., rows and columns,columnar, hypercube, linked list, tree, etc.) that may be madetraversable using any of a variety of mechanisms to find a particulardata point. The data set 1330 may incorporate the metadata 1335, whichmay include a description of the manner in which the data of the dataset 1330 is organized.

The size of the data set 1330 may be sufficiently large that processingthe data set 1330 using a single processing device may be deemed highlyimpractical. Indeed, it may be that the data set 1330 also changesfrequently enough over time (e.g., is updated hourly, daily, weekly,etc.) such that the length of time required to process the data set 1330using a single processing device would yield results that would alreadybe out of date before such processing could be completed. Thus, it maybe deemed highly desirable to process the data set 1330 in a distributedand at least partially parallel manner using a group of interconnectedprocessing devices (sometimes referred to as a “grid”), such as thedistributed processing system 1000 of either FIG. 11A or 11B. As will beexplained in greater detail, the manner in which the storage andretrieval of the data set 1330 is effected advantageously obviates theneed for coordination among the node devices 1700 and minimizes thecoordination required between the node devices 1700 and the controldevice 1500. This contributes to enabling the node devices 1700 tostore, retrieve and process separate data set portions 1732 of the dataset 1330 at least partially in parallel. Furthermore, the overheadrequired to store the map data 1510 which enables the accurate andflexible distribution of data blocks and/or the data sub-blocksrepresenting data set portions 1732 is usually relatively small comparedto the total size of the data set 1330. Therefore, the making of thetradeoff of storing the map data 1510 may result in comparativelysignificant improved retrieval performance and flexibility thatoutweighs the relatively small cost associated with creating and storingthe map data. Although the degree of parallelism may be impacted byworkload and environmental constraints common to various computingsystems, parallelism during storage and retrieval more readily scaleswith progressively larger forms of the data set 1330 and/or as thequantity of node devices 1700 increases. The time required to request apointer from the control device 1500 may be significantly smaller thanthe time to store or retrieve the corresponding data block(s) and/ordata sub-block(s).

The data within the data set 1330 may be organized in a manner thatenables such parallel distributed processing. More specifically, theorganization of the data within the data set 1330 may enable thedivision of the data set 1330 into multiple ones of the data setportions 1732 (with varying degrees of flexibility, as will beexplained) in which each of the data set portions 1732 is able to beprocessed without dependencies on the results of the processing of anyof the other data set portions 1732. As a result, the data set portions1732 may each be distributable to any of the node devices 1700 withoutregard to which one of the node devices 1700 that any of the other dataset portions 1732 are distributed to. Such divisibility of the data set1330 obviates the need to incur the latencies of serializing theprocessing of two or more of the data set portions 1732, as well asobviating the latencies of transferring an output of the processing ofone data set portion 1732 by one node device 1700 through the network1999 to another node device 1700 at which another data set portion 1732is to be processed.

Such divisibility of the data set 1330 may also enable the exchange ofthe data set portions 1732 between the multiple node devices 1700 andthe one or more storage devices 1100, either for storage or retrieval ofthe data set 1330, in a distributed and at least partially parallelmanner. More specifically, each of the data set portions 1732 may beexchanged between one of the node devices 1700 and the one or morestorage devices 1100 without regard to whether or when any of the otherdata set portions 1732 has been similarly exchanged between another ofthe node devices 1700 and the one or more storage devices 1100. Tobetter enable such distributed and at least partially parallel exchangesof the data set portions 1732, the data set portions 1732 and theinformation required to access the data set portions 1732 may be storedwithin the data file 1110 in a manner that minimizes dependencies amongthe control device 1500 and the multiple node devices 1700 in thestorage and retrieval of the data set portions 1732 and such associatedinformation.

Referring to both FIGS. 12A and 12B, the data file 1110 may include afile header 1111 and a payload section 1113. The one or more storagedevices 1100 may employ any of a variety of file systems in storing andmanaging access to files within the one or more storage devices 1100,including and not limited to, network file system (NFS), block devicestorage, any of the various versions of file allocation table (FAT),High Sierra Format (ISO-9660), write anywhere file layout (WAFL), XFS,etc. The file header 1111 may include indications of any of a variety ofdetails of the data file 1110 that may be germane to, and that may beorganized in compliance with the specifications of, one of the filesystems employed by the one or more storage devices 1100.

The payload section 1113 may be a single contiguous series of bytes thatoccupies the majority of data file 1110, and depending on variousaspects of the file system employed by the one or more storage devices1100, the starting end of the payload section 1113 may follow at leastthe file header 1111. At the starting end, a first quantity of kilobytesof the payload section 1113 may be occupied by the base map 1115 thatprovides at least a portion of the map data 1510 that describes themanner in which the data set portions 1732 are organized within thepayload section 1113. Such a first quantity of kilobytes of the payloadsection 1113 may be followed by a second quantity of kilobytes of thepayload section 1113 that may be occupied by the metadata 1335.Following these two quantities of kilobytes may then be at least onecontiguous series of the data blocks 1131

In some embodiments, the manner in which the data of the data set 1330is organized within the data set 1330 may be relatively highly granular,thereby providing a relatively high degree of flexibility in thedivision of the data set 1330 into the data set portions 1732. By way ofexample, where the data of the data set 1330 is organized into rows andcolumns with a relatively large quantity of rows, a relatively highdegree of granularity may be provided based on distribution of the rowsamong the data set portions 1732. With such a relatively high degree offlexibility in defining the data set portions 1732, the quantity and/orsize of each data set portion 1732 may be more tightly correlated to thequantity of the node devices 1700 available at the time the data set1330 is generated and/or to the resources within each of those availablenode devices 1700.

However, in other embodiments, the data of the data set 1330 may beorganized within the data set 1330 in a manner that has relatively lowgranularity, thereby providing a relatively low degree of flexibility inthe division of the data set 1330 into the data set portions 1732. As aresult, the quantity of data set portions 1732 into which the data set1330 may be divided, while still avoiding dependencies in processingtherebetween, may be relatively limited such that at least some of thedata set portions 1732 may be required to be relatively large. Such anembodiment of the data set 1330 may be described as being made up ofpartitioned data in which the relatively limited opportunities fordivision of the data set 1330 may define a relatively low quantity ofpartitions. An example of such partitioning may be an embodiment of thedata set 1330 in which the data is partitioned such that it is divisibleinto no more than fifty data set portions 1732 that each correspond toone of the fifty states of the United States. The characteristics of thedata within each of those partitions may be such that the data withinone of the partitions may be processed with no dependencies on the datawithin any of the other partitions. However, the processing of the datawithin any one of the partitions may require access to at least asubstantial portion of the data therein such that the data within eachof the partitions cannot be distributed across more than one node device1700 without a relatively high likelihood that time consuming exchangesof data would be required thereamong.

FIG. 12A depicts an example embodiment of the organization of the dataof the data set 1330 within the data file 1110 where the data of thedata set 1330 is of relatively high granularity such that the data ofthe data set 1330 is deemed to be non-partitioned data. For such anon-partitioned embodiment, each of the data blocks 1131 in thecontiguous series of the data blocks 1131 (including the depicted datablocks 1131 a and 1131 b) that follows at least the base map 1115 andthe metadata 1335 may correspond to a single data set portion 1732 thatmay be processed by one of the node devices 1700. As will be explainedin greater detail, each of the node devices 1700 may act independentlyof the other node devices 1700 to store a single data set portion 1732within the payload section 1113 as a single corresponding data block1131 (e.g., the depicted single data block 1131 a), or to store multipledata set portions 1732 within the payload section 1113 as multiplecorresponding data blocks 1131 (e.g., the depicted multiple adjacentdata blocks 1131 b).

The control device 1500 may coordinate such independent actions by thenode devices 1700 by providing each node device 1700 with at least onepointer at which the node device 1700 may so store one or more of thedata set portions 1732. After coordinating the storage of all of thedata set portions 1732 that are to be stored by the node devices 1700through the distribution of pointers, the control device 1500 may storeat least the base map 1115 and/or the metadata 1335 within the payloadsection 1113. As will be explained in greater detail, the control device1500 may generate portions of the contents of the base map 1115 as thecontrol device 1500 generates pointers and provides those pointers tothe node devices 1700 for use in storing the data set portions 1732.

The base map 1115 may include a contiguous series of bytes. At thestarting end of the base map 1115, a first quantity of bytes of the basemap 1115 may be occupied by an indication of the map size 1515 thatspecifies how many bytes, words, doublewords, etc. in total are used toprovide a map of the data blocks 1131 within the payload section 1113.Following such a first quantity of bytes may be a second quantity ofbytes of the base map 1115 that are occupied by indications of one ormore map parameters 1516 that may include an indication that the data ofthe data set 1330 is non-partitioned data. Following these first twosuch quantities of bytes may then be a series of map entries 1511(including the depicted map entries 1511 a and 1511 b). The order of themap entries 1511 within at least the base map 1115 may correspond to theorder of the data blocks 1131 within the payload section 1113.

For non-partitioned data within the data set 1330, it may be deemedlikely that there will be a relatively high quantity of data setportions 1732, and therefore, a correspondingly relatively high quantityof data blocks 1131. It may also be deemed likely that among thenumerous data blocks 1131 will be numerous instances of multipleadjacent ones of the data blocks 1131 within the payload section 1113that are of identical size. Thus, in an effort to take advantage of suchlikely characteristics of the data blocks 1131 to reduce the overallstorage space consumed by a map of the data blocks 1131, each map entry1511 may include an indication of a data block size specifying a size inbytes, words, doublewords, etc. and a data block count specifying aquantity of adjacent ones of the data blocks 1131 within the payloadsection 1113 that are of the specified data block size. Thus, thedepicted map entry 1511 a that corresponds to the data block 1131 a mayspecify a data block count of 1 and the size of just the data block 1131a, while the depicted map entry 1511 b that corresponds to the trio ofadjacent data blocks 1131 b may specify a data block count of 3 and thesingle identical size of all three of the data blocks 1131 b.

FIG. 12B depicts an example embodiment of the organization of the dataof the data set 1330 within the data file 1110 where the data of thedata set 1330 is of relatively low granularity such that the data of thedata set 1330 is deemed to be partitioned data divided into multiplepartitions 1333. As previously discussed, the data of the data set 1330within each partition 1333 may need to be processed by a single one ofthe node devices 1700 such that the data of the data set 1330 withineach partition 1333 cannot be distributed among multiple ones of thenode devices 1700. It may also be deemed likely that there will be widevariations in size among the partitions 1333 (e.g., as a result of thedata including strings of widely varying character length, linked listsof widely varying quantities of entries, tree data structures withwidely varying quantities of branches, etc.). Thus, while one of thenode devices 1700 may be caused to process the data within a singlelarge partition 1333, another of the node devices 1700 may be caused toprocess the data within multiple significantly smaller partitions 1333.In recognition of such differences between partitioned data andnon-partitioned data, the manner in which an embodiment of the data set1330 made up of partitioned data may be stored within the data file 1110may differ from the manner in which an embodiment of the data set 1330made up of non-partitioned data may be stored. More specifically, forpartitioned data, the quantity and/or size of each data set portion 1732may be more tightly correlated to the quantity and/or sizes of thepartitions 1333.

Thus, for such a partitioned embodiment, each of the data blocks 1131 inthe contiguous series of the data blocks 1131 that follows at least thebase map 1115 and the metadata 1335 may include one or more datasub-blocks 1133, and each data sub-block 1133 may correspond to a singledata set portion 1732. As will be explained in greater detail, each ofthe node devices 1700 may act independently of the other node devices1700 to store a single data set portion 1732 within the payload section1113 as a single corresponding data sub-block 1133 within a single datablock 1131, or to store multiple data set portions 1732 within thepayload section 1113 as multiple corresponding data sub-blocks 1133within a single data block 1131. Again, the control device 1500 maycoordinate such independent actions by the node devices 1700 byproviding each node device 1700 with at least one pointer at which thenode device 1700 may so store one or more of the data set portions 1732as one or more data sub-blocks 1133 within a single data block 1131.After coordinating the storage of all of the data set portions 1732 thatare to be stored by the node devices 1700 through the distribution ofpointers, the control device 1500 may store at least the base map 1115and/or the metadata 1335 within the payload section 1113. The controldevice 1500 may also store a data header 1112 that provides indicationsof the quantity of node devices 1700 that are involved in storing thedata set 1330 within the payload section 1113. As depicted, in variousembodiments, such a data header 1112 may form part of the file header1111 or part of the payload section 1113 (e.g., part of the map base1115 or part of the metadata 1335).

Such differences in the manner in which an embodiment of the data set1330 made up of partitioned data is stored from the manner in which anembodiment of the data set 1330 made up of non-partitioned data isstored may be accompanied by corresponding differences in the content ofthe base map 1115. More specifically, among the indications of one ormore map parameters 1516 may be an indication that the data of the dataset 1330 is partitioned data. Again, following the two quantities ofbytes at which the base map 1115 and the metadata 1335 are stored may bea series of map entries 1511 that may correspond to the order of thedata blocks 1131 within the payload section 1113. However, each mapentry 1511 may correspond solely to a single data block 1131, and mayinclude a data sub-block count specifying a quantity of one or moreadjacent ones of the data sub-blocks 1133 that are included within thesingle corresponding data block 1131. Following the sub-block countwithin each map entry 1511 may be a series of one or more mapsub-entries 1513 that each correspond to one of the data sub-blocks 1133within the corresponding data block 1131, and the order of those mapsub-entries 1513 may correspond to the order of the data sub-blocks 1133within the corresponding data block 1131. Each such map sub-entry 1513may include an indication of the size of the corresponding datasub-block 1133 and a hashed identifier indicative of the partition 1333to which the data within the corresponding data sub-block 1133 belongs.

In such a partitioned embodiment, each partition 1333 may be given aunique label that provides a form of unique identification. However,just as the data within the data set 1330 may be any of a variety oftypes of data, the labels given to each partition 1333 may take any of avariety of forms, including and not limited to, numerical values and/oralpha-numeric text that may be of any arbitrary length. The hashedidentifiers may be normalized versions of those labels, and may begenerated in some embodiments by taking a hash of the labels, and/or byperforming any of a variety of other functions on those labels in otherembodiments.

Referring again to both FIGS. 12A and 12B, in various embodiments, thequantity of data blocks 1131 and/or of data sub-blocks 1133 may becomerelatively numerous that a relatively large quantity of storage spacewithin the payload section 1113 may need to be allocated to accommodatea correspondingly large quantity of map entries 1511 within the base map1115. In some embodiments, additional space for the storage of mapentries 1511 beyond what can be accommodated within the base map 1115may be provided at one or more other locations within the payloadsection 1113.

More specifically, and referring to FIG. 12C, one or more map extensions1117 may be positioned among the base map 1115 and the metadata 1335,and/or may be interspersed among the data blocks 1131 within the payloadsection 1113. As depicted, the map entries 1511 that may otherwise bestored within the base map 1115 may, instead, be stored within the firstof the map extensions 1117 to be stored within the payload section 1113following the base map 1115. This may be done to make room within thebase map 1115 for a series of extension pointers 1517 that each providean indication of the location of one of the map extensions 1117 withinthe payload section, and the order of the extension pointers 1517 withinthe base map 1115 may coincide with the order of the map extensions 1117within the payload section 1113.

In some embodiments, each map extension 1117 may be required to bestored within the payload section 1113 at a location that is ahead ofthe locations of all of the data blocks 1131 for which the map extension1117 includes map entries 1511 to enable more efficient retrieval of oneor more of those data blocks 1131 from within the payload section 1113.In some embodiments, the base map 1115 and each of the map extensions1117 may share a common size. In other embodiments, the first mapextension 1117 following the base map 1115 within the payload section1113 may have a size that is double the size of the base map 1115, andeach additional map extension 1117 may have a size that is double thesize of the preceding map extension 1117 within the payload section1113. As a result, in embodiments in which the payload section 1113includes multiple map extensions 1117, the size of the map extensions1117 from the first to the last may grow exponentially. Where such apredictable pattern of increasing size in the map extensions 1117 isused, there may be no need to store an indication within the base map1115 of the sizes of each of the map extensions 1117.

FIGS. 13A-E, together, illustrate an example of storing an embodiment ofthe data set 1330 made up of non-partitioned data in embodiments of thedistributed processing system 1000 of FIG. 11A or 11B in greater detail.More specifically, FIGS. 13A and 13B, together, depict aspects of thestorage of a single data set portion 1732 by a single node device 1700.FIGS. 13C and 13D, together, depict aspects of the storage of multipledata set portions 1732 by a single node device 1700. FIG. 13E depictsaspects of the storage of the map data 1510 by the control device 1500(or the controller 1500).

As recognizable to those skilled in the art, the control routines 1540and 1740, including the components of which each is composed, areselected to be operative on whatever type of processor or processorsthat are selected to implement applicable ones of the processorcomponents 1550 and/or 1750. In various embodiments, each of theseroutines may include one or more of an operating system, device driversand/or application-level routines (e.g., so-called “software suites”provided on disc media, “applets” obtained from a remote server, etc.).Where an operating system is included, the operating system may be anyof a variety of available operating systems appropriate for theprocessor components 1550 and/or 1750. Where one or more device driversare included, those device drivers may provide support for any of avariety of other components, whether hardware or software components, ofthe node devices 1700 and/or the control device 1500 (or the controller1500 incorporated into one of the node devices 1700).

Turning to FIG. 13A, as depicted, the control routine 1740 may include atask component 1745 to perform processing tasks as directed by thecontrol device 1500, and a persisting component 1741 to effect storageof a data set portion 1732 that may have been generated through aperformance of a task by the task component 1745. Correspondingly, thecontrol routine 1540 may include a coordinating component 1545 tocoordinate the at least partially parallel distributed performances ofvarious tasks among multiple ones of the node devices 1700, and amapping component 1541 to coordinate the at least partially parallel anddistributed performances of storage and retrieval of data set portions1732 by the multiple ones of the node devices 1700.

In some embodiments, upon completion of a processing task involving adata set portion 1732 of the data set 1330, the task component 1745 mayoperate the network interface 1790 of the node device 1700 to transmitan indication of such completion to the control device 1500 via thenetwork 1999. In embodiments in which the completed task includes thegeneration of the data set portion 1732, the task component 1745 maytransmit at least a portion of the metadata 1335 that describes aspectsof the organization of data within the data set portion 1732 to thecontrol device 1500 via the network 1999. Additionally, in response tosuch completion of the processing task by the task component 1745, thepersisting component 1741 may operate the network interface 1790 totransmit a request to the control device 1500 for a pointer to alocation within the payload section 1113 of the data file 1110 (see FIG.12A) at which to store the data set portion 1732. In so doing, thepersisting component 1741 may transmit an indication of the size of thedata set portion 1732 along with the request to provide the controldevice 1500 with an indication of how much storage space is neededwithin the payload section 1113 to store the data set portion 1732 as adata block 1131.

Within the control device 1500, the coordinating component 1545 mayoperate the network interface 1590 to recurringly monitor for receivedindications of the status of node devices 1700, and may maintainindications of the current state of each node device 1700 as part of thenode data 1530. In response to receiving the indication of completion ofthe processing task involving the data set portion 1732 from the nodedevice 1700, the coordinating component 1545 may update an indication ofthe current status of the node device 1700 within the node data 1530 toreflect such completion. Additionally, the mapping component 1541 mayoperate the network interface 1590 to recurringly monitor for requestsfor pointers. In response to receiving the request for a pointer fromthe node device 1700 for use in storing the data set portion 1732, themapping component 1541 may employ indications earlier stored within themap data 1510 of portions of the payload section 1113 that have alreadybeen allocated to identify a location within the payload section 1113 atwhich the data set portion 1732 may be stored. The mapping component1541 may then operate the network interface 1590 to transmit a pointerto that identified location back to the node device 1700 via the network1999. The mapping component 1541 may then also update the map data 1510with an indication of where the data set portion 1732 is to be storedwithin the payload section 1113 to enable the subsequent identificationof another location within the payload section 1113 at which anotherdata set portion 1732 may be stored and for which another pointer may beprovided in response to another request from another node device 1700.

In response to receiving the pointer transmitted from the control device1500 in response to the earlier transmitted request for a pointer, thepersisting component 1741 may store an indication of the receivedpointer within the pointer data 1735. Turning to FIG. 13B, as depicted,the persisting component 1741 may then operate the network interface1790 to transmit the data set portion 1732 to the one or more storagedevices 1100 along with a command to the one or more storage devices1100 to store the data set portion 1732 as a data block 1131 at thelocation within the payload section 1113 that is specified by thepointer. It should be noted that although FIG. 13B depicts an example ofthe node device 1700 storing the single data set portion 1732 ofnon-partitioned data as a single data block 1131, other embodiments arepossible in which the node device 1700 may store multiple data setportions 1732 of non-partitioned data.

Turning to FIG. 13C, as depicted, embodiments are possible in which atleast one of multiple node devices 1700 (e.g., the depicted node device1700 y) stores a single data set portion 1732 of an embodiment of thedata set 1330 made up of non-partitioned data as a single data block1131, while at least one other of the multiple node devices 1700 (e.g.,the depicted node devices 1700 x and 1700 z) stores multiple data setportions 1732 thereof as corresponding multiple data blocks 1131. Alsodepicted in FIG. 13C is an example of how the timing of the transmittingof requests to the control device 1500 for pointers may result ininterspersing of data blocks 1131 from different node devices 1700within the payload section 1113. More specifically, upon completion ofperforming one or more processing tasks involving data set portions 1732a and 1732 b, the depicted node device 1700 x may have requested a pairof pointers to a pair of adjacent locations within the payload section1113 at which to store the data set portions 1732 a and 1732 b asadjacent data blocks 1131 a and 1131 b. Alternatively, upon completionof such performance, the node device 1700 x may have requested a singlepointer to a single location within the payload section 1113 largeenough thereat to store both of the data set portions 1732 a and 1732 bas the adjacent data blocks 1131 a and 1131 b.

In contrast, upon completion of performing one or more processing tasksinvolving data set portion 1732 d, and before completion of the same oneor more processing tasks involving data set portion 1732 e, the depictednode device 1700 z may have requested a single pointer to a singlelocation within the payload section 1113 at which to store the data setportion 1732 d as data block 1131 d. Then, before the node device 1700 zis able to complete such processing involving data set portion 1732 eand/or request another single pointer to another single location withinthe payload section 1113 at which to store the data set portion 1732 eas the data block 1131 e, the depicted node device 1700 y may completesuch processing of data set portion 1732 c and may request a pointer toa location within the payload section 1113 at which to store the dataset portion 1732 c as the data block 1131 c. As a result, the nodedevice 1700 y may be provided with a pointer for use in storing the dataset portion 1732 c before the node device 1700 z is provided with apointer for use in storing the data set portion 1732 e. This may lead tothe data block 1131 c being stored at a location within the payloadsection 1113 that is interposed between the locations at which the datablocks 1131 d and 1131 e are stored.

It should be noted that the timing by which requests for pointers arereceived at the control device 1500 and/or by which the control device1500 transmits the requested pointers back to the ones of the nodedevices 1700 that requested them does not necessarily control the timingby which corresponding data set portions 1732 are stored within thepayload section 1113. More specifically, any of a variety of factors maycause one node device 1700 to more quickly make use of a receivedpointer to a location within the payload section 1113 than another nodedevice 1700. Thus, a data set portion 1732 for which a pointer was laterreceived may at least begin to be stored before another data set portion1732 for which a pointer was received earlier.

Turning to FIG. 13D, a single node device 1700 may output the depictedmultiple data set portions 1732 a-d as a result of performing multipleinstances of a processing task at least partially in parallel within thesingle node device 1700 in which each instance generates one of themultiple data set portions 1732 a-d. More specifically, as depicted,each of multiple instances of the task component 1745 a-d may beexecuted in a separate thread of execution by the processor component1750 of the single node device 1700, and/or the processor component 1750may incorporate multiple cores 1755 a-d that are each capable ofexecuting one of the instances of the task component 1745 a-dindependently of the others. Thus, in such embodiments, the single oneof the node devices 1700 may internally function in a manner akin tomultiple ones of the node devices 1700 in generating the multiple dataset portions 1732 a-d.

In some of such embodiments, the multiple instances of the taskcomponent 1745 a-d may be capable of coordinating thereamong to theextent of causing the persisting component 1741 to combine what mightotherwise be multiple separate requests for multiple separate pointersinto a single request for a single pointer for all of the multiple dataset portions 1732 a-d. The persisting component 1741 may then operatethe network interface 1790 to transmit such a single request to thecontrol device 1500 for a single pointer for use in storing all of themultiple data set portions 1732 a-d as adjacently located data blocks1131 a-d within the payload section 1113. Such combining into a singlerequest in which the multiple data set portions 1732 a-d are then causedto be stored as a single data block 1131 may be deemed advantageous byallowing the one or more storage devices 1100 to determine a relativelyoptimal organization of the storage of that resulting data block 1131among the one or more storage devices 1100 based on the configuration ofstorage components therein, including and not limited to, a relativelyoptimal splitting of that resulting data block 1131 among more than onestorage component. The fact of the multiple data set portions 1732 a-dalso being transmitted by the depicted node device 1700 as a single datablock 1131 may also allow some degree of optimization in thetransmission to be arrived at between the depicted node device 1700 andthe one or more storage devices 1100, thereby addressing possible issuesof contention among the node devices 1700 as each acts at leastpartially in parallel to store one or more data blocks 1131. In some ofsuch embodiments, the request may specify only a single size that is asum of the sizes of all of the data set portions 1732 a-d, while inothers of such embodiments, the request may separately specify the sizesof alternatively may include specifications of a separate size for eachdata set portion 1732 a-d. However, in other embodiments, the multipleinstances of the task component 1745 a-d may not be capable of suchcoordination (or may simply have not been architected to engage in suchcoordination) such that each causes the persisting component 1741 totransmit a separate request for a separate pointer for use in separatelystoring each of the multiple data set portions 1732 a-d. As discussedwith regard to FIG. 3C, the use of such separate requests for pointersmay result in the multiple data set portions 1732 a-d being storedwithin the payload section 1113 in a manner that is not contiguous.

Turning to FIG. 13E, following the provision of pointers for the storageof all data set portions 1732 of the non-partitioned embodiment of thedata set 1330, the mapping component 1541 may operate the networkinterface 1590 to transmit the map data 1510 to the one or more storagedevices 1100 for storage within the payload section 1113 as at least thebase map 1115. However, as previously discussed in reference to FIG.12C, where the map data 1510 becomes relatively large in the amount ofstorage required to store it within the payload section 1113, the mapdata 1510 may alternatively be stored as a combination of the base map1115 and one or more map extensions 1117. In addition to storing the mapdata 1510 as at least the base map 1115, the mapping component 1541 mayalso operate the network interface 1590 to transmit the metadata 1335 tothe one or more storage devices 1100 for storage within the payloadsection 1113.

In some embodiments, the mapping component 1541 may operate the networkinterface 1590 to recurringly monitor for indications from each nodedevice 1700 of not needing to request any more pointers from the controldevice 1500. In such embodiments, the mapping component 1541 may delaythe storage of at least the map data 1510 until indications have beenreceived from all of the multiple node devices 1700 involved inprocessing the non-partitioned embodiment of the data set 1330 thatthere will be no more requests for pointers. However, in embodiments inwhich each of the node devices 1700 is required to request only a singlepointer for all data set portions 1732 that are to be stored by thatnode device 1700, the control device 1500 may determine whether thereare more data set portions 1732 for which pointers remain to berequested based on whether or not requests for pointers have beenreceived from all of the node devices 1700 involved in processing thedata set 1330. Thus, in such embodiments, exchanges of informationbetween the control device 1500 and the node devices 1700 through thenetwork 1999 for purposes of coordinating at least the storage of thedata set 1330 may advantageously be further minimized by elimination ofthe need for exchanges of explicit indications of whether there are moredata set portions 1732 for which pointers remain to be requested.

FIGS. 14A-E, together, illustrate an example of retrieving an embodimentof the data set 1330 made up of non-partitioned data in embodiments ofthe distributed processing system 1000 of FIG. 11A or 11B in greaterdetail. More specifically, FIGS. 14A and 14B, together, depict aspectsof the collection of information needed by the control device 1500 todetermine a distribution of data set portions 1732 among available onesof the node devices 1700. FIG. 14C depicts aspects of transmission ofthe pointers to available ones of the node devices 1700. FIG. 14Ddepicts aspects of the retrieval of one or more data set portions 1732by a single node device 1700. FIG. 14E depicts aspects of an approach toeffecting a relatively balanced distribution of the data set portions1732 among available ones of the node devices 1700.

Turning to FIG. 14A, within each node device 1700 of multiple nodedevices 1700, the task component 1745 may operate the network interface1790 to recurringly transmit indications of the current status of thenode device 1700 to the control device 1500 via the network 1999. Suchrecurring transmissions may convey an indication of the availability ofthe node device 1700 to perform tasks on one or more portions of a dataset.

Within the control device 1500, the coordinating component 1545 mayoperate the network interface 1590 to recurringly monitor for receivedindications of the status of node devices 1700, and may maintain andrecurringly update indications of the current state of each node device1700 as part of the node data 1530. More specifically, the coordinatingcomponent 1545 may recurringly monitor for indications of whether eachnode device 1700 of multiple node devices 1700 is available to beassigned to perform operations on a portion of a data set as part of adistributed and at least partially parallel performance of a processingtask involving multiple portions of a data set, such as the embodimentof the data set 1330 made up of non-partitioned data.

Turning to FIG. 14B, as part of retrieving the non-partitioned data ofsuch an embodiment of the data set 1330, the mapping component 1541 mayoperate the network interface 1590 to retrieve the base map 1115 (andany accompanying map extensions 1117—see FIG. 12C) via the network 1999from the payload section 1113 of the data file 1110 stored within theone or more storage devices 1100. As previously discussed, the base map1115 (and any accompanying map extensions 1117) may provide a map of themanner in which the multiple data set portions 1732 of thenon-partitioned embodiment of the data set 1330 are stored within thepayload section 1113 as multiple data blocks 1131, and the mappingcomponent 1541 may store such a map as the map data 1510. Additionally,the mapping component 1541 may operate the network interface 1590 toretrieve the metadata 1335 that describes aspects of the organization ofdata within the data set 1330 via the network 1999 from the payloadsection 1113.

Turning to FIG. 14C, the coordinating component 1545 may refer to therecurringly updated indications of status of multiple node devices 1700in the node data 1530 to determine which ones of the multiple nodedevices 1700 are currently available to perform a processing task on oneor more data set portions 1732 of the non-partitioned embodiment of thedata set 1330. The coordinating component 1545 may then operate thenetwork interface 1590 to transmit an indication of what the processingtask is to the available ones of the node devices 1700 via the network1999. In so doing, the coordinating component 1545 may also distributecopies of at least a portion of the metadata 1335 to each of thoseavailable node devices 1700.

Additionally, the mapping component 1541 may operate the networkinterface 1590 to transmit, to the available ones of the node devices1700, one or more pointers to data blocks 1131 within the payloadsection 1113. In so doing, the mapping component 1541 may refer to themap data 1510 to identify the locations within the payload section 1113at which each of the pointers point to enable retrieval of the datablocks 1131 therefrom. In some embodiments, the mapping component 1541may derive such locations for each data block 1131 within the payloadsection 1113, at least in part, by summing the sizes specified in themap data 1510 for all the data blocks 1131 that precede each data block1131. The mapping component 1541 may receive indications of which onesof the multiple node devices 1700 are the available ones from thecoordinating component 1545 or may directly retrieve such indicationsfrom the node data 1530. Each transmission of a pointer may include anindication of the size of the data block(s) 1131 pointed to by thatpointer to enable each of the available ones of the node devices 1700 toretrieve the correct amount of data when retrieving each of the datablocks 1131 from the payload section 1113.

Within each node device 1700, the task component 1745 may operate thenetwork interface 1790 to recurringly monitor for received indicationsfrom the control device 1500 of a task to perform, and may locally storeany portion of the metadata 1335 received via the network 1999 for usein performing such a task. As depicted, the control routine 1740 mayadditionally include a retrieval component to effect retrieval of one ormore data set portions 1732 from the payload section 1113, in which theone or more data set portions 1732 may be stored as one or morecorresponding data blocks 1131, for use in the performance of a task bythe task component 1745. The retrieval component may operate the networkinterface 1790 to recurringly monitor for any transmissions of pointersfrom the control device 1500 via the network 1999, and may store anysuch received pointers as part of the pointer data 1735.

Turning to FIG. 14D, which depicts a single example one of the availablenode devices 1700, in response to receiving one or more pointers to oneor more data blocks 1131 within the payload section 1113, the retrievalcomponent 1743 may operate the network interface 1790 to retrieve theone or more data blocks 1131 from the payload section 1113. In so doing,the retrieval component 1743 may transmit one or more commands to theone or more storage devices 1100 to provide the one or more data blocks1131, employing the one or more pointers and/or the accompanyingindications of size to specify the one or more data blocks 1131 to beprovided. The retrieval component 1743 may locally store each of theretrieved data blocks 1131 as a data set portion 1732 for use by thetask component 1745 in performing the task specified to the node device1700 by the control device 1500.

How many of the data blocks 1131 are retrieved by each of the availableones of the node devices 1700 from the payload section 1113 may bedetermined by the manner in which pointers to the data blocks 1131 aredistributed among the available ones of the node devices 1700 by thecontrol device 1500. Turning to FIG. 14E, in some embodiments, thepointers may be distributed in a round robin manner to the availableones of the node devices 1700. It should be noted that FIG. 14E depictsa relatively simplistic example of distribution of among only three nodedevices 1700 a-c in a round robin for purposes of illustration. It isenvisioned that a considerably greater quantity of node devices 1700would more likely be used. This approach may be deemed desirable due toits simplicity of implementation and/or as an approach to distributingthe data set portions 1732 of the non-partitioned embodiment of the dataset 1330 among the available ones of the node devices 1700 in relativelysimilar quantities.

FIGS. 15A-E, together, illustrate an example of storing an embodiment ofthe data set 1330 made up of partitioned data in embodiments of thedistributed processing system 1000 of FIG. 11A or 11B in greater detail.More specifically, FIGS. 15A and 15B, together, depict aspects of thestorage of a single data set portion 1732 by a single node device 1700.FIG. 15C depicts aspects of the storage of multiple data set portions1732 by a single node device 1700. FIGS. 15D and 15E, together, depictaspects of the storage of the map data 1510 by the control device 1500(or the controller 1507).

Turning to FIG. 15A, in some embodiments, upon completion of aprocessing task involving a data set portion 1732 of the data set 1330,the task component 1745 may operate the network interface 1790 of thenode device 1700 to transmit an indication of such completion to thecontrol device 1500 via the network 1999. In embodiments in which thecompleted task includes the generation of the data set portion 1732, thetask component 1745 may transmit to the control device 1500 at least aportion of the metadata 1335 that describes aspects of the organizationof data within the data set portion 1732, including which partition 1333(see FIG. 12B) the data set portion 1732 belongs to. Additionally, inresponse to such completion of the processing task by the task component1745, the persisting component 1741 may operate the network interface1790 to transmit a request to the control device 1500 for a pointer to alocation within the payload section 1113 of the data file 1110 (see FIG.12B) at which to store the data set portion 1732.

In transmitting the request for a pointer to the control device 1500,the persisting component 1741 may transmit an indication of the size ofthe data set portion 1732 along with the request to provide the controldevice 1500 with an indication of how much storage space is neededwithin the payload section 1113 to store the data set portion 1732 as adata sub-block 1133 within a data block 1131. Further, the persistingcomponent 1741 may additionally transmit a hashed identifier generatedfrom the label of the partition 133 to which the data set portion 1732belongs. As depicted, in some embodiments, the persisting component 1741may include a hash component 1742 to generate such hashed identifiersfrom the unique labels provided to each of one or more partitions 1333of the partitioned data. In such embodiments, the hash component 1742may take a hash of (or perform any of a variety of other normalizationoperations with) the partition label of the partition to which the dataset portion 1732 belongs to generate the corresponding hashed identifierthat the persisting component 1741 may transmit to the control device1500 in the request for a pointer.

Within the control device 1500, the mapping component 1541 may store thehashed identifier as part of the map data 1510 in a manner thatassociates the hashed identifier with the data set portion 1732 and thepartition 1333 to which the data set portion 1732 belongs. Also withinthe control device 1500, the coordinating component 1545 may operate thenetwork interface 1590 to recurringly monitor for received indicationsof the status of node devices 1700, and may maintain indications of thecurrent state of each node device 1700 as part of the node data 1530. Inresponse to receiving the indication of completion of the processingtask involving the data set portion 1732 from the node device 1700, thecoordinating component 1545 may update an indication of the currentstatus of the node device 1700 to reflect such completion within thenode data 1530. Additionally, in response to receiving the request for apointer from the node device 1700 for use in storing the data setportion 1732, the mapping component 1541 may employ indications earlierstored within the map data 1510 of portions of the payload section 1113that have already been allocated to identify a location within thepayload section 1113 at which the data set portion 1732 may be stored.More specifically, the mapping component 1541 may derive such locationsfor each data sub-block 1133 within the payload section 1113, at leastin part, by summing the sizes specified in the map data 1510 for allpreceding data sub-blocks 1133. The mapping component 1541 may thenoperate the network interface 1590 to transmit a pointer to thatidentified location back to the node device 1700 via the network 1999.The mapping component 1541 may then also update the map data 1510 withan indication of where the data set portion 1732 is to be stored withinthe payload section 1113 to enable the subsequent identification ofanother location within the payload section 1113 at which another dataset portion 1732 may be stored and for which another pointer may beprovided in response to another request from another node device 1700.

In response to receiving the pointer transmitted from the control device1500 in response to the earlier transmitted request for a pointer, thepersisting component 1741 may store an indication of the receivedpointer within the pointer data 1735. Turning to FIG. 15B, as depicted,the persisting component 1741 may then operate the network interface1790 to transmit the data set portion 1732 to the one or more storagedevices 1100 along with a command to the one or more storage devices1000 to store the data set portion 1732 as a data sub-block 1133 withina data block 1131 at the location within the payload section 1113 thatis specified by the pointer. It should be noted that although FIG. 15Bdepicts an example of the node device 1700 storing the single data setportion 1732 as a single data sub-block 1133, other embodiments arepossible in which the node device 1700 may store multiple data setportions 1732 of the partitioned embodiment of the data set 1330 asmultiple corresponding data sub-blocks 1133 within the single data block1131.

Turning to FIG. 15C, in some embodiments, the node device 1700 mayoutput the depicted multiple data set portions 1732 a-d as a result ofperforming multiple instances of a processing task at least partially inparallel within the single node device 1700 in which each instancegenerates one of the multiple data set portions 1732 a-d. Morespecifically, as depicted, each of multiple instances of the taskcomponent 1745 a-d may be executed in a separate thread of execution bythe processor component 1750 of the single node device 1700, and/or theprocessor component 1750 may incorporate multiple cores 1755 a-d thatare each capable of executing one of the instances of the task component1745 a-d independently of the others. Thus, in such embodiments, thesingle one of the node devices 1700 may internally function in a mannerakin to multiple ones of the node devices 1700 in generating themultiple data set portions 1732 a-d.

In such embodiments, the multiple instances of the task component 1745a-d may coordinate to cause the persisting component 1741 to transmit asingle request to the control device 1500 for a single pointer for usein storing all of the multiple data set portions 1732 a-d as adjacentlylocated data sub-blocks 1133 a-d within a single data block 1131 withinthe payload section 1113. The request may include separate indicationsof a hashed identifier for each of the data set portions 1732 a-d. Whereall of the multiple data set portions 1732 a-d belong to the samepartitions 1333, the same hashed identifier may be indicated in therequest for all of the data set portions 1732 a-d. However, wheredifferent ones of the multiple data set portions 1732 a-d belong todifferent partitions 1333, different hashed identifiers may be indicatedfor different ones of the data set portions 1732 a-d.

Turning to FIG. 15D, following the provision of pointers for the storageof all data set portions 1732 of the partitioned embodiment of the dataset 1330 and/or following receipt of indications from the node devices1700 involved in storing the data set 1330 that all data blocks 1131and/or data sub-blocks 1133 have been successfully stored within thepayload section 1113 of the data file 1110, the mapping component 1541may operate the network interface 1590 to transmit the map data 1510 tothe one or more storage devices 1100 for storage within the payloadsection 1113 as at least the base map 1115. However, as previouslydiscussed in reference to FIG. 12C, where the map data 1510 becomesrelatively large in the amount of storage required to store it withinthe payload section 1113, the map data 1510 may alternatively be storedas a combination of the base map 1115 and one or more map extensions1117, as depicted in FIG. 15E.

Returning to FIG. 15D, in addition to storing the map data 1510 as atleast the base map 1115, the mapping component 1541 may also operate thenetwork interface 1590 to transmit the metadata 1335 to the one or morestorage devices 1100 for storage within the payload section 1113.Further, the mapping component 1541 may also store indications of thequantity of node devices 1700 among which all of the data set portions1732 of the data set 1330 were temporarily stored and/or were generatedas the data header 1112. Again, in various embodiments, the data header1112 may be incorporated into either the file header 1111 or the payloadsection 1113 (e.g., within the map base 1115 or as part of the metadata1335). Regardless of where the indication of the quantity of nodedevices 1700 is stored, in some embodiments, the indication of whetherthe data of the data set 1330 is partitioned data or non-partitioneddata may be combined with the indication of the quantity of node devices1700. More specifically, in such embodiments, an indication of a zeroquantity of node devices 1700 may serve as an indication that the dataof the data set 330 is non-partitioned data. In contrast, an indicationof a non-zero quantity of node devices 1700 may serve as an indicationthat the data set 330 is partitioned data, in addition to specifying thequantity of node devices 1700. This manner of combining these twoindications may be employed where an indication of the quantity of nodedevices 1700 is deemed superfluous where the data is non-partitioneddata.

In some embodiments, the mapping component 1541 may operate the networkinterface 1590 to recurringly monitor for indications from each nodedevice 1700 of not needing to request any more pointers from the controldevice 1500. In such embodiments, the mapping component 1541 may delaythe storage of at least the map data 1510 until indications have beenreceived from all of the multiple node devices 1700 involved inprocessing the partitioned embodiment of the data set 1330 that therewill be no more requests for pointers. However, in embodiments in whicheach of the node devices 1700 is required to request only a singlepointer for all data set portions 1732 that are to be stored by thatnode device 1700, the control device 1500 may determine whether thereare more data set portions 1732 for which pointers remain to berequested based on whether or not requests for pointers have beenreceived from all of the node devices 1700 involved in processing thedata set 1330. Again, in such embodiments, exchanges of informationbetween the control device 1500 and the node devices 1700 through thenetwork 1999 for purposes of coordinating at least the storage of thedata set 1330 may advantageously be further minimized by elimination ofthe need for exchanges of explicit indications of whether there are moredata set portions 1732 for which pointers remain to be requested. Again,an advantage of requiring only a single request be made by each nodedevice 1700 for a pointer, thereby resulting in the handling of multipledata blocks 1131 together in the storage thereof may enable furtheroptimization of such storage by the one or more storage devices 1100,and/or may enable further optimization of the transmission thereofbetween the node device 1700 and the one or more storage devices 1100through the network 1999 that is responsive to competing transmissionsof data by each of the node devices 1700 to the one or more storagedevices 1100.

FIGS. 16A-D, together, illustrate an example of retrieving an embodimentof the data set 1330 made up of partitioned data in embodiments of thedistributed processing system 1000 of FIG. 11A or 11B in greater detail.More specifically, FIG. 16A depicts aspects of the collection ofinformation needed by the control device 1500 to determine adistribution of data set portions 1732 among available ones of the nodedevices 1700. FIG. 16B depicts aspects of transmission of the pointersto available ones of the node devices 1700. FIG. 16C depicts aspects ofan approach to effecting a relatively balanced distribution of the dataset portions 1732 among available ones of the node devices 1700. FIG.16D depicts aspects of the retrieval of one or more data set portions1732 by a single node device 1700.

Turning to FIG. 16A, as part of retrieving the data set 1330 in such apartitioned embodiment, the mapping component 1541 may operate thenetwork interface 1590 to retrieve the base map 1115 (and anyaccompanying map extensions 1117—see FIG. 12C) via the network 1999 fromthe payload section 1113 of the data file 1110 stored within the one ormore storage devices 1100. As previously discussed, the base map 1115(and any accompanying map extensions 1117) may provide a map of themanner in which the multiple data set portions 1732 of the partitionedembodiment of the data set 1330 are stored within the payload section1113, and the mapping component 1541 may store such a map as the mapdata 1510. The mapping component 1541 may additionally operate thenetwork interface 1590 to retrieve the metadata 1335, describing aspectsof the organization of data within the data set 1330 via the network1999 from the payload section 1113. Alternatively or additionally, themapping component 1541 may additionally operate the network interface1590 to retrieve the data header 1112, which (if present) may describethe quantity of node devices 1700 that most recently stored the data set1330 within the payload section 1113 of the data file 1110. Again, invarious embodiments, the data header 1112 may be incorporated into oneor both of the base map 1115 and the metadata 1335.

Turning to FIG. 16B, the coordinating component 1545 may refer torecurringly updated indications of status of multiple node devices 1700maintained within the node data 1530 to determine which ones of themultiple node devices 1700 are currently available to perform aprocessing task on one or more data set portions 1732 of the partitionedembodiment of the data set 1330. The coordinating component 1545 maythen operate the network interface 1590 to transmit an indication of theprocessing task to the available ones of the node devices 1700 via thenetwork 1999. In so doing, the coordinating component 1545 may alsodistribute copies of at least a portion of the metadata 1335 to each ofthose available node devices 1700.

The mapping component 1541 may first make a determination of which oftwo approaches to use in distributing data set portions 1732 of the dataset 1330 among the currently available node devices 1700, andaccordingly, which of two approaches to use in deriving and distributingpointers among the currently available node devices 1700. To do so, themapping component 1541 may compare the quantity of the node devices 1700that are currently available to the quantity of node devices 1700 thatwere involved in most recently storing the data set 1330 within the onedata file 1110. If these two quantities of the node devices 1700 match,then the mapping component 1541 may make the determination to distributethe data set portions 1732 among the currently available node devices1700 in a manner that effectively recreates the distribution of the dataset portions 1732 that existed at the time the data set 1330 was mostrecently stored within the data file 1110. More precisely, the mappingcomponent 1541 may distribute each entire data block 1131 within thepayload section 1113 of the data file 1110 (thereby keeping together alldata sub-blocks 1133 within each data block 1131) to a different one ofthe currently available node devices 1700. However, if these twoquantities of the node devices 1700 do not match, then the mappingcomponent 1541 may make the determination to derive a new distributionof individual ones of the data sub-blocks 1133 within each of the datablocks 1131 within the payload section 1113 of the data file 1110 amongthe currently available node devices 1700 (to thereby individuallydistribute each of the data set portions 1732).

Turning to both FIGS. 16B and 16C, to effect either such a distributionof whole data blocks 1131 or such a distribution of individual ones ofthe data sub-blocks 1133 among the currently available node devices1700, the mapping component 1541 may employ at least a subset of thehashed identifiers associated by the map data 1510 with each of the datasub-blocks 1133. The mapping component 1541 may assign positive integervalues as identifiers to each of the available node devices 1700,starting with the integer value of 0 and incrementing by the integervalue of 1 for each such node device 1700. As depicted, the mappingcomponent 1541 may include a division component 1543 to perform integerdivision in which hashed identifiers are divided by the quantity ofcurrently available node devices 1700 to derive a modulo value from eachsuch division.

More precisely, where the quantities of currently available node devices1700 and of the node devices 1700 most recently involved in storing thedata set 1330 do match, then for each of the data blocks 1131, themapping component 1541 may retrieve a single hashed identifierassociated by the map data 1510 with one of the data sub-blocks 1133within that data block 1131, and the division component 1543 may dividethat single hashed identifier by the quantity of currently availablenode devices 1700 to derive a modulo value. The mapping component 1541may then match that modulo value to one of the positive integer valuesassigned to one of the currently available node devices 1700. Themapping component 1541 may then operate the network interface 1590 totransmit a pointer to the location of that data block 1131 within thepayload section 1113 to that one of the node devices 1700 which had beenassigned the matching one of the positive integer values.

In embodiments in which the data of the data set 330 is partitioned, andwhere there are one or more instances of data belonging to more than onepartition 1333 being generated and/or processed by the same node device1700, there may be a limitation on which partitions 1333 of data of thedata set 330 may be generated and/or stored within the same node device1700. The limitation may be that all partitions 1333 of data that soshare the same node device 1700 must have partition labels that begetthe same modulo value when the hashed identifiers derived from thosepartition labels (e.g., by taking hashes of those partition labels) aredivided by the quantity of currently available node devices 1700. Thus,the use of only a single hashed identifier associated with only one ofthe data sub-blocks 1133 within each data block 1131 in deriving amodulo value by which the distribution of the entire data block 1131 isdetermined may rely on this requirement to ensure that it makes nodifference which hashed identifier among all of those associated witheach of the data sub-blocks 1133 is so used.

However, where the quantities of currently available node devices 1700and of the node devices 1700 most recently involved in storing the dataset 1330 do not match, then for each of the data sub-blocks 1133, themapping component 1541 may retrieve the hashed identifier associated bythe map data 1510 with that data sub-block 1133, and the divisioncomponent 1543 may divide the hashed identifier by the quantity ofcurrently available node devices 1700 to derive a modulo value. Themapping component 1541 may then match that modulo value to one of thepositive integer values assigned to one of the currently available nodedevices 1700. The mapping component 1541 may then operate the networkinterface 1590 to transmit a pointer to the location of that datasub-block 1133 within the payload section 1113 to that one of the nodedevices 1700 which had been assigned the matching one of the positiveinteger values.

Such use of the hashed identifiers of each of the data sub-blocks 1133to determine distribution of each of the data sub-block 1133,individually, may result in the derivation of a new distribution of thedata set portions 1732 that is a relatively balanced distribution ofdata among the available node devices 1700. Also, the fact that all ofthe data sub-blocks 1133 associated with a single partition 1333 willhave the same hashed identifier, such use of modulo values taken of thehashed identifiers ensures that all data belonging to any one of thepartitions 1333 will be distributed to the same one of the availablenode devices 1700, and not among multiple node devices 1700.

Turning to FIG. 16D, in response to receiving one or more pointers toone or more data blocks 1131 or data sub-blocks 1133 within the payloadsection 1113, the retrieval component 1743 may operate the networkinterface 1790 to retrieve those one or more data blocks 1131 or datasub-blocks 1133 from the payload section 1113. In so doing, theretrieval component 1743 may transmit one or more commands to the one ormore storage devices 1100 to provide the one or more data blocks 1131 ordata sub-blocks 1133, employing the one or more pointers and/or theaccompanying indications of size to specify the one or more data blocks1131 or data sub-blocks 1133 to be provided. The retrieval component1743 may locally store each of the retrieved data sub-blocks 1133 as adata set portion 1732 for use by the task component 1745 in performingthe task specified to the node device 1700 by the control device 1500.

Returning to FIGS. 11A and 11B, in various embodiments, each of theprocessor components 1550 and 1750 may include any of a wide variety ofcommercially available processors. Further, one or more of theseprocessor components may include multiple processors, a multi-threadedprocessor, a multi-core processor (whether the multiple processor corescoexist on the same or separate dies), and/or a multi-processorarchitecture of some other variety by which multiple physically separateprocessors are linked.

However, in a specific embodiment, the processor component 1550 of thecontrol device 1500 may be selected to efficiently perform thederivation of distributions of data set portions 1732. Alternatively oradditionally, the processor component 1750 of each of the node devices1700 may be selected to efficiently perform processing tasks withmultiple data set portions in parallel. By way of example, the processorcomponent 1550 and/or 1750 may incorporate a single-instructionmultiple-data (SIMD) architecture, may incorporate multiple processingpipelines, and/or may incorporate the ability to support multiplesimultaneous threads of execution per processing pipeline. Alternativelyor additionally by way of example, the processor component 1750 of atleast one of the node devices 1700 may incorporate multi-threadedcapabilities and/or multiple processor cores to enable parallelperformances of the functions of both the control device 1500 and a nodedevice 1700.

In various embodiments, each of the storages 1560 and 1760 may be basedon any of a wide variety of information storage technologies, includingvolatile technologies requiring the uninterrupted provision of electricpower, and/or including technologies entailing the use ofmachine-readable storage media that may or may not be removable. Thus,each of these storages may include any of a wide variety of types (orcombination of types) of storage device, including without limitation,read-only memory (ROM), random-access memory (RAM), dynamic RAM (DRAM),Double-Data-Rate DRAM (DDR-DRAM), synchronous DRAM (SDRAM), static RAM(SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), flash memory, polymermemory (e.g., ferroelectric polymer memory), ovonic memory, phase changeor ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS)memory, magnetic or optical cards, one or more individual ferromagneticdisk drives, non-volatile storage class memory, or a plurality ofstorage devices organized into one or more arrays (e.g., multipleferromagnetic disk drives organized into a Redundant Array ofIndependent Disks array, or RAID array). It should be noted thatalthough each of these storages is depicted as a single block, one ormore of these may include multiple storage devices that may be based ondiffering storage technologies. Thus, for example, one or more of eachof these depicted storages may represent a combination of an opticaldrive or flash memory card reader by which programs and/or data may bestored and conveyed on some form of machine-readable storage media, aferromagnetic disk drive to store programs and/or data locally for arelatively extended period, and one or more volatile solid state memorydevices enabling relatively quick access to programs and/or data (e.g.,SRAM or DRAM). It should also be noted that each of these storages maybe made up of multiple storage components based on identical storagetechnology, but which may be maintained separately as a result ofspecialization in use (e.g., some DRAM devices employed as a mainstorage while other DRAM devices employed as a distinct frame buffer ofa graphics controller).

However, in a specific embodiment, the storage 1760 of one or more ofthe node devices 1700 that stores one or more of the data set portions1732 may be implemented with a redundant array of independent discs(RAID) of a RAID level selected to provide fault tolerance to preventloss of one or more of these datasets and/or to provide increased speedin accessing one or more of these datasets.

In various embodiments, the network interfaces 1590 and 1790 may employany of a wide variety of communications technologies enabling thesedevices to be coupled to other devices as has been described. Each ofthese interfaces includes circuitry providing at least some of therequisite functionality to enable such coupling. However, each of theseinterfaces may also be at least partially implemented with sequences ofinstructions executed by corresponding ones of the processor components(e.g., to implement a protocol stack or other features). Whereelectrically and/or optically conductive cabling is employed, theseinterfaces may employ timings and/or protocols conforming to any of avariety of industry standards, including without limitation, RS-232C,RS-422, USB, Ethernet (IEEE-802.3) or IEEE-1394. Where the use ofwireless transmissions is entailed, these interfaces may employ timingsand/or protocols conforming to any of a variety of industry standards,including without limitation, IEEE 802.11a, 802.11ad, 802.11ah,802.11ax, 802.11b, 802.11g, 802.16, 802.20 (commonly referred to as“Mobile Broadband Wireless Access”); Bluetooth; ZigBee; or a cellularradiotelephone service such as GSM with General Packet Radio Service(GSM/GPRS), CDMA/1×RTT, Enhanced Data Rates for Global Evolution (EDGE),Evolution Data Only/Optimized (EV-DO), Evolution For Data and Voice(EV-DV), High Speed Downlink Packet Access (HSDPA), High Speed UplinkPacket Access (HSUPA), 4G LTE, etc.

However, in a specific embodiment, the network interface 1790 of one ormore of the node devices 1700 that stores one or more of the data setportions 1732 may be implemented with multiple copper-based orfiber-optic based network interface ports to provide redundant and/orparallel pathways in exchanging one or more of the data set portions1732 with the one or more storage devices 1100.

In various embodiments, the division of processing and/or storageresources among the control device 1500 and/or the node devices 1700,and/or the API architectures supporting communications among the controldevice 1500 and/or the node devices 1700, may be configured to and/orselected to conform to any of a variety of standards for distributedprocessing, including without limitation, IEEE P2413, AllJoyn, IoTivity,etc. By way of example, a subset of API and/or other architecturalfeatures of one or more of such standards may be employed to implementthe relatively minimal degree of coordination described herein toprovide greater efficiency in parallelizing processing of data, whileminimizing exchanges of coordinating information that may lead toundesired instances of serialization among processes. However, it shouldbe noted that the organization and manner of representation ofinformation within the data map 1510, as well as its usage in enablingparallelization of storage, retrieval and/or processing of data setportions 1732 of the data set 1330 are not dependent on, nor constrainedby, existing API architectures and/or supporting communicationsprotocols. More broadly, there is nothing in the inherit structure ofthe map data 1510, the metadata 1335, or the manner in which the dataset 1330 may be organized in storage, transmission and/or distributionthat is bound to existing API architectures or protocols.

FIG. 17 illustrates an example embodiment of a logic flow 2100. Thelogic flow 2100 may be representative of some or all of the operationsexecuted by one or more embodiments described herein. More specifically,the logic flow 2100 may illustrate operations performed by the processorcomponent 1750 in executing the control routine 1740, and/or performedby other component(s) of at least one of the node devices 1700.

At 2110, a processor component of a node device (e.g., the processorcomponent 1750 of one of the node devices 1700) may transmit a requestto a control device or to a controller implemented within another nodedevice (e.g., the control device 1500, or the controller 1507 acting inplace of the control device 1500 from within another of the node devices1700) for a pointer to a location within a data file maintained by oneor more storage devices (e.g., the data file 1110 maintained by the oneor more storage devices 1100) at which the node device may store one ormore data set portions of a data set (e.g., one or more of the data setportions 1732 of the data set 1330). As previously discussed, inembodiments in which the data of the data set is not partitioned, eachdata set portion may be stored as a data block (e.g., as data blocks1131), and the node device may include an indication of the size (e.g.,in bytes, words, doublewords, etc.) of each of the one or more data setportions to be stored starting at the location that will be pointed toby the requested pointer. However, as also previously discussed, inembodiments in which the data of the data set is partitioned, each dataset portion may be stored as a data sub-block of a data block (e.g., asdata sub-blocks 1133 within a data block 1131), and the node device mayinclude indications of individual sizes for each data set portion to bestored, along with a hashed identifier generated by the node device fromthe partition label associated with each data set portion.

At 2120, the requested pointer may be received at the node device fromthe control device (or controller within another node device). At 2130,in response to having received the requested pointer, the processorcomponent of the node device may transmit the one or more data setportions to the one or more storage devices with an instruction to theone or more storage devices to store the one or more data set portionsat the location pointed to by the pointer as one or more data blocks oras one or more data sub-blocks within a data block.

At 2140, the processor component may check whether there are more dataset portions to be stored that were not included in the last request fora pointer transmitted to the control device (or controller withinanother node device). As previously discussed, multiple instances of aprocessing task involving different data set portions may be performedwithin a single node device, and may result in a need to transmit morethan one request for a pointer. Again, such multiple instances may besupported by multi-threaded execution and/or by multiple processor cores(e.g., the multiple processor cores 1755) of the processor component ofthe node device. If, at 2140, there are still one or more data setportions to be stored, then the processor component may return totransmitting a request for a pointer at 2110. Alternatively, as alsopreviously discussed, coordination among such multiple instances of aprocessing task within the node device may coordinate such that only onesuch request is made that includes all of the data set portions of thedata set that are processed and/or generated within the node device,such that the check at 2140 is not performed. Again, it may be that eachnode device is required to make only one request for a pointer that isto be used to store all data set portions processed and/or generatedwithin the node device, and this requirement may be relied upon by thecontrol device (or controller within another node device) as the basisfor determining whether all requests for pointers have been received.

FIG. 18 illustrates an example embodiment of a logic flow 2200. Thelogic flow 2200 may be representative of some or all of the operationsexecuted by one or more embodiments described herein. More specifically,the logic flow 2200 may illustrate operations performed by the processorcomponent 1750 in executing the control routine 1740, and/or performedby other component(s) of at least one of the node devices 1700.

At 2210, a processor component of a node device (e.g., the processorcomponent 1750 of one of the node devices 1700) may receive, from acontrol device or a controller implemented within another node device(e.g., the control device 1500 or the controller 1500 within another ofthe node devices 1700), a pointer to one or more data set portions of adata set stored within a data file (e.g., data set portions 1732 of thedata set 1330 stored within the data file 1110) to be retrievedtherefrom. As previously discussed, in embodiments in which the data ofthe data set is not partitioned, the pointer may be to a single data setportion stored in the data file as a data block, and the pointer may beaccompanied by an indication of the size of the data block. However, asalso previously discussed, in embodiments in which the data of the dataset is partitioned, the pointer may be to a single data sub-block withina data block, and the pointer may be accompanied by an indication of thesize of the data sub-block.

At 2220, the processor component may transmit a request to the one ormore storage devices to provide the data block or data sub-block thatstarts at the location in the data file pointed to by the pointer, andincluding the quantity of data specified by the indication of size thataccompanied the pointer. At 2230, the requested data block or datasub-block may be received at the node device from the one or morestorage devices. At 2240, the processor component may locally store thereceived data block or data sub-block as a data set portion to beprocessed by the processor component in a processing task specified bythe control device (or controller within another node device).

FIGS. 19A and 19B, together, illustrate an example embodiment of a logicflow 2300. The logic flow 2300 may be representative of some or all ofthe operations executed by one or more embodiments described herein.More specifically, the logic flow 2300 may illustrate operationsperformed by the processor component 1550 in executing the controlroutine 1540, and/or performed by other component(s) of the controldevice 1500 or the controller 1500 implemented within at least one ofthe node devices 1700.

At 2310, a processor component of a control device or a controllerimplemented within a node device (e.g., the processor component 1550 ofthe control device 1500 or of the controller 1507) may receive a requestfor a pointer to a location within a data file maintained by one or morestorage devices (e.g., the data file 1110 maintained by the one or morestorage devices 1100) at which the node device may store one or moredata set portions of a data set (e.g., one or more of the data setportions 1732 of the data set 1330). As previously discussed, inembodiments in which the data of the data set is not partitioned, eachdata set portion may be stored as a data block (e.g., as data blocks1131), and the node device may include with the request an indication ofthe size (e.g., in bytes, words, doublewords, etc.) of the one or moredata set portions to be stored starting at the location that will bepointed to by the requested pointer. However, as also previouslydiscussed, in embodiments in which the data of the data set ispartitioned, each data set portion may be stored as a data sub-blockwithin a data block (e.g., as data sub-blocks 1133 within a data block1131), and the node device may include with the request indications ofindividual sizes for each data set portion to be stored, along with ahashed identifier generated by the node device from the partition labelfor each data set portion.

Thus, if at 2320, the data of the data set is not partitioned, then at2322, the processor component may derive the location within the datafile at which to store the data set portion for which the pointer wasrequested as a data block based on a total of the sizes of all of thedata blocks previously stored in the data file, and may generate apointer to point to that location. The processor component may thentransmit that pointer to the node device.

At 2330, the processor component may perform a check of whether the sizeof the data block for which the pointer was requested is the same asthat of the immediately preceding and adjacent data block in the datafile. If so, then at 2332, the processor component may increment a blockcount of adjacent data blocks of the same size in the map entry thatcorresponds to that immediately preceding and adjacent data block in amap of the data blocks within the data file (e.g., one of the mapentries 1511 in the map stored as the map data 1510). However, if thesize of the data block for which the pointer was requested is not thesame as that of the immediately preceding and adjacent data block in thedata file, then at 2334, the processor component may generate a new mapentry in the map that includes an indication of the size of the datablock for which the pointer was requested and a block count of one blockof that size.

At 2340, following either an incrementing of a block count at 2332 orthe addition of a new map entry in the map at 2334, if there are stillmore data set portions of the non-partitioned data to be stored as datablocks, then the processor component may await the reception of anotherrequest for a pointer at 2310. As previously discussed, each of the nodedevices may transmit an indication to the control device (or thecontroller within one of the node devices) of whether there are stillmore data set portions for which requests for pointers are to be made.If, at 2340, there are no more data set portions of the partitioned datato be stored as data blocks, then the processor component may transmitthe map of the data blocks to the one or more storage devices to bestored as a map base and/or one or more map extensions, depending on theamount of storage space needed to store the map.

Returning to 2320, if the data of the data set is partitioned, then at2350, the processor component may derive the location within the datafile at which to store the one or more data set portions as one or moredata sub-blocks based on a total of the sizes of all of the datasub-blocks previously stored in the data file, and may generate apointer to point to that location. The processor component may thentransmit that pointer to the node device.

At 2360, the processor component may generate a new map entry in the mapfor a new data block that includes a separate sub-entry (e.g., aseparate sub-entry 1513) for each data sub-block associated with one ofthe data set portions for which the pointer was requested. Eachsub-entry may include an indication of the size of its correspondingdata sub-block, and a hashed identifier generated by the node devicefrom the partition label for each data set portion.

At 2340, following the addition of a new block entry in the map at 2360,if there are still more data set portions of the partitioned data to bestored as data sub-blocks, then the processor component may await thereception of another request for a pointer at 2310. However, if at 2340,there are no more data set portions of the partitioned data to be storedas data sub-blocks, then the processor component may transmit the map ofthe data blocks and data sub-blocks within those data blocks to the oneor more storage devices to be stored as a map base and/or one or moremap extensions, depending on the amount of storage space needed to storethe map. As previously discussed, for partitioned data, the processorcomponent may also store an indication of a quantity of the node devicesinvolved in storing the data set.

FIGS. 20A, 20B and 20C, together, illustrate an example embodiment of alogic flow 2400. The logic flow 2400 may be representative of some orall of the operations executed by one or more embodiments describedherein. More specifically, the logic flow 2400 may illustrate operationsperformed by the processor component 1550 in executing the controlroutine 1540, and/or performed by other component(s) of the controldevice 1500 or the controller 1500 implemented within at least one ofthe node devices 1700.

At 2410, a processor component of a control device or a controllerimplemented within a node device (e.g., the processor component 1550 ofthe control device 1500 or of the controller 1507) may receiveindications from multiple node devices (e.g., the node devices 1700)concerning their current availability to perform processing tasks on aportion of a data set (e.g., the data set portions 1732 of the data set1330). As previously discussed, each node device may recurringlytransmit indications of its current status, including its availabilityto perform processing tasks on a portion of a data set.

At 2412, the processor component may retrieve, from a data filemaintained within one or more storage devices (e.g., the data file 1110maintained by the one or more storage devices 1100), a map of datablocks and/or data sub-blocks, and metadata of a data set (e.g., the mapbase 1115 and any map extensions 1117, and the metadata 1335).Additionally, the processor component may retrieve an indication of thequantity of node devices that were involved in the most recent storageof the data set in the data file (e.g., the data header 1112, or again,the metadata 1335). As previously discussed, in embodiments in which thedata of the data set is not partitioned, each data set portion may bestored in the data file as a data block (e.g., each data set portion1732 as a data block 1131), and the map may provide indications of sizesof data blocks and/or block counts of adjacent sets of data blocks thathave the same size. However, as also previously discussed, inembodiments in which the data of the data set is partitioned, each dataset portion may be stored as a data sub-block within a data block (e.g.,as a data sub-block 1133 within a data block 1131), and the map mayprovide indications of size and hashed identifiers for each datasub-block within each data block.

Thus, if at 2420, the data of the data set is not partitioned, then at2422, the processor component may retrieve a single map entrycorresponding to a single data block from the map at 2422 (e.g., asingle map entry 1511). At 2424, the processor component may select oneof the available node devices 2424 in a round robin manner to which todistribute the single data block. At 2426, the processor component mayderive the location within the data file from which to retrieve thesingle data block based on a total of the sizes of all of the datablocks stored in preceding locations within the data file, and maygenerate a pointer to point to that location. At 2428, the processorcomponent may then transmit that pointer to the selected node device. At2430, if there is another map entry in the map, then the processorcomponent may retrieve that next map entry at 2422.

However, if at 2420, the data of the data set is partitioned, then at2440, the processor component may assign a series of increasing positiveinteger values (specifically, the series 0, 1, 2, 3, etc., created byrepeated incrementing by the positive integer value of 1) to each of theavailable node devices. At 2450, the processor component may thenperform a check of whether the quantity of currently available nodedevices matches the quantity of node devices that were last involved instoring the data set within the data file.

If at 2450, the two quantities of node devices match, then thedistribution of the data set that existed at the time the data set wasmost recently stored may be recreated among the available node devicesby the processor component. At 2452, the processor component mayretrieve a single map entry corresponding to a single data block fromthe map. At 2454, the processor component may derive the location withinthe data file from which to retrieve the data block based on a total ofthe sizes of all of the data blocks in preceding locations within thedata file, and may generate a pointer to point to the data block.

At 2456, the processor component may divide a hashed identifierassociated by the map with one of the data sub-blocks within the datablock by the quantity of available node devices (thereby treating thehashed identifier as a positive integer value), and derive a modulovalue from the division operation. At 2458, the processor component maythen transmit that pointer to the one of the available node devices thatwas assigned (at 2440) an integer value from the series of integervalues that matches the modulo value.

At 2460, if there is another map entry in the map, then the processorcomponent may retrieve that map entry at 2452.

However, if at 2450, the two quantities of node devices do not match,then a derivation of a new distribution of the data set among theavailable node devices may be performed by the processor component. At2470, the processor component may retrieve a single map entrycorresponding to a single data block from the map, and may then retrievea single sub-entry corresponding to a single data sub-block from withinthat single map entry (e.g., a single map sub-entry 1513 from within asingle map entry 1511) at 2472. At 2474, the processor component mayderive the location within the data file from which to retrieve the datasub-block based on a total of the sizes of all of the data sub-blocks inany data blocks stored in preceding locations within the data file, andmay generate a pointer to point to the data sub-block.

At 2476, the processor component may divide a hashed identifierassociated by the map with the data sub-block by the quantity ofavailable node devices (thereby treating the hashed identifier as apositive integer value), and derive a modulo value from the divisionoperation. At 2478, the processor component may then transmit thatpointer to the one of the available node devices that was assigned (at2440) an integer value from the series of integer values that matchesthe modulo value.

At 2480, if there is another map sub-entry within the map entry, thenthe processor component may retrieve that next map sub-entry at 2472. Ifthere isn't another map sub-entry in the map entry at 2480, then at2490, if there is another map entry in the map, then the processorcomponent may retrieve that map entry at 2470.

Some systems may use Hadoop®, an open-source framework for storing andanalyzing big data in a distributed computing environment. Some systemsmay use cloud computing, which can enable ubiquitous, convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, servers, storage, applications and services)that can be rapidly provisioned and released with minimal managementeffort or service provider interaction. Some grid systems may beimplemented as a multi-node Hadoop® cluster, as understood by a personof skill in the art. Apache™ Hadoop® is an open-source softwareframework for distributed computing.

What has been described above includes examples of the disclosedarchitecture. It is, of course, not possible to describe everyconceivable combination of components and/or methodologies, but one ofordinary skill in the art may recognize that many further combinationsand permutations are possible. Accordingly, the novel architecture isintended to embrace all such alterations, modifications and variationsthat fall within the spirit and scope of the appended claims.

1. An apparatus comprising a processor component and a storage to storeinstructions that, when executed by the processor component, cause theprocessor component to perform operations comprising: analyze metadataindicative of an organization of data within a data set or map dataindicative of an organization of multiple data blocks of the data setwithin a data file to determine whether the data set comprisespartitioned data; determine whether the analyzed metadata indicateswhether the data set comprises partitioned data, wherein when the dataset comprises partitioned data the data set is organized into multiplepartitions and each whole partition is distributable to a single nodedevice to be processed; and in response to a determination that data setdoes not comprise partitioned data, wherein the map data comprisesmultiple map entries in which each map entry corresponds to one or moredata blocks of the multiple data blocks, perform operations comprising:for each map entry of the map data, retrieve, from the map entry, a datablock size and a data block quantity, wherein the data block quantityindicates a quantity of adjacent data blocks of the multiple data blockswithin the data file that correspond to the map entry; and for each datablock that corresponds to the map entry: determine a location of thecorresponding data block within the data file; select one of a firstquantity of node devices that are currently available to perform aprocessing task; and provide a pointer to the selected one of the firstquantity of node devices, wherein the pointer comprises: an indicationof the location of the corresponding data block within the data file;and the data block size.
 2. The apparatus of claim 1, wherein theselection of one of the first quantity node devices comprises a roundrobin selection of one of the first quantity of node devices.
 3. Theapparatus of claim 1, wherein the processor component is caused toperform operations comprising: in response to a determination that thedata set comprises partitioned data, perform operations comprising:compare the first quantity of node devices to a second quantity of nodedevices that were last involved in storage of the data set within thedata file; assign a numerical designation value to each node device ofthe first quantity of node devices; and in response to a match betweenthe first and second quantities of node devices, for each data block ofthe multiple data blocks, perform operations comprising: retrieve, fromthe map data, a hashed identifier for one data sub-block indicated bythe map data to be within the data block, wherein: the data sub-blockcomprises data of the data set that belongs to a partition of themultiple partitions; and the hashed identifier is derived from apartition label of the partition; retrieve, from the map data, a datasub-block size for each of the data sub-blocks indicated by the map datato be within the data block; determine a location of the data blockwithin the data file; divide the hashed identifier by the first quantityof node devices to obtain a modulo value; and transmit a pointer to anode device of the first quantity of node devices that is assigned adesignation value that matches the modulo value, wherein the pointercomprises: an indication of the location of the data block within thedata file; and a sum of data sub-block sizes of the data sub-blockswithin the data block.
 4. The apparatus of claim 3, wherein in responseto the determination that the data set comprises partitioned data and inresponse to a lack of a match between the first and second quantities ofnode devices, the processor component is caused to perform operationscomprising: for each data sub-block within each data block of themultiple data blocks, perform operations comprising: retrieve, from themap data, the data sub-block size and hashed identifier of the datasub-block; determine a location of the data sub-block within the datafile; divide the hashed identifier by the first quantity of node devicesto obtain a modulo value; and provide a pointer to the node of the firstquantity of node devices that is assigned a designation value thatmatches the modulo value, wherein the pointer comprises: an indicationof the location of the data sub-block within the data file; and the datasub-block size of the data sub-block.
 5. The apparatus of claim 1,wherein: the apparatus comprises a node device of the first quantity ofnode devices; and the processor component is caused to retrieve, via anetwork, a portion of the data set from the data file as one of thefirst quantity of node devices at least partially in parallel with atleast one other node device of the first quantity of node devices. 6.The apparatus of claim 5, wherein the processor component is caused toperform the processing task with a portion of the data set retrievedfrom the data file as the one of the first quantity of node devices atleast partially in parallel with at least one other node device of thefirst quantity of node devices.
 7. The apparatus of claim 1, wherein:the data file is maintained by one or more storage devices; and theprocessor component is caused to retrieve, from the one or more storagedevices through a network, the map data and the metadata.
 8. Theapparatus of claim 7, wherein, to retrieve the map data from the datafile, the processor component is caused to perform operationscomprising: transmit, via the network, a first command to the one ormore storage devices to provide a map base of the data map from the datafile; receive, via the network, a map base from the data file; analyzethe map base to determine whether at least a portion of the map data isstored within one or more map extensions within the data file; and inresponse to a determination that at least a portion of the map data isstored within one or more map extensions, perform operations comprising:transmit, via the network, a second command to the one or more storagedevices to provide at least one map extension of the one or more mapextensions; and receive, via the network, the at least one map extensionfrom the data file.
 9. The apparatus of claim 1, comprising a controldevice coupled to a grid of multiple node devices, wherein the processorcomponent is caused to perform operations comprising: recurringlyreceive, via a network, indications of availability to performprocessing tasks from each node device of the multiple node devices;recurringly update a stored indication of availability of each nodedevice of the multiple node devices; and analyze the stored indicationsof availability to identify the first quantity of node devices.
 10. Theapparatus of claim 9, wherein the processor component is caused toperform operations comprising provide an indication of the processingtask to the first quantity of node devices to enable more than one nodedevice of the first quantity of node devices to each perform theprocessing task with a portion of the data set at least partially inparallel.
 11. A computer-program product tangibly embodied in anon-transitory machine-readable storage medium, the computer-programproduct including instructions operable to cause a processor componentto perform operations comprising: analyze metadata indicative of anorganization of data within a data set or map data indicative of anorganization of multiple data blocks of the data set within a data fileto determine whether the data set comprises partitioned data; determinewhether the analyzed metadata indicates whether the data set comprisespartitioned data, wherein when the data set comprises partitioned datathe data set is organized into multiple partitions and each wholepartition is distributable to a single node device to be processed; andin response to a determination that data set does not comprisepartitioned data, wherein the map data comprises multiple map entries inwhich each map entry corresponds to one or more data blocks of themultiple data blocks, perform operations comprising: for each map entryof the map data, retrieve, from the map entry, a data block size and adata block quantity, wherein the data block quantity indicates aquantity of adjacent data blocks of the multiple data blocks within thedata file that correspond to the map entry; and for each data block thatcorresponds to the map entry: determine a location of the correspondingdata block within the data file; select one of a first quantity of nodedevices that are currently available to perform a processing task; andprovide a pointer to the selected one of the first quantity of nodedevices, wherein the pointer comprises: an indication of the location ofthe corresponding data block within the data file; and the data blocksize.
 12. The computer-program product of claim 11, wherein theselection of one of the first quantity node devices comprises a roundrobin selection of one of the first quantity of node devices.
 13. Thecomputer-program product of claim 11, wherein the processor component iscaused to perform operations comprising: in response to a determinationthat the data set comprises partitioned data, perform operationscomprising: compare the first quantity of node devices to a secondquantity of node devices that were last involved in storage of the dataset within the data file; assign a numerical designation value to eachnode device of the first quantity of node devices; and in response to amatch between the first and second quantities of node devices, for eachdata block of the multiple data blocks, perform operations comprising:retrieve, from the map data, a hashed identifier for one data sub-blockindicated by the map data to be within the data block, wherein: the datasub-block comprises data of the data set that belongs to a partition ofthe multiple partitions; and the hashed identifier is derived from apartition label of the partition; retrieve, from the map data, a datasub-block size for each of the data sub-blocks indicated by the map datato be within the data block; determine a location of the data blockwithin the data file; divide the hashed identifier by the first quantityof node devices to obtain a modulo value; and transmit a pointer to anode device of the first quantity of node devices that is assigned adesignation value that matches the modulo value, wherein the pointercomprises: an indication of the location of the data block within thedata file; and a sum of data sub-block sizes of the data sub-blockswithin the data block.
 14. The computer-program product of claim 13,wherein in response to the determination that the data set comprisespartitioned data and in response to a lack of a match between the firstand second quantities of node devices, the processor component is causedto perform operations comprising: for each data sub-block within eachdata block of the multiple data blocks, perform operations comprising:retrieve, from the map data, the data sub-block size and hashedidentifier of the data sub-block; determine a location of the datasub-block within the data file; divide the hashed identifier by thefirst quantity of node devices to obtain a modulo value; and provide apointer to the node of the first quantity of node devices that isassigned a designation value that matches the modulo value, wherein thepointer comprises: an indication of the location of the data sub-blockwithin the data file; and the data sub-block size of the data sub-block.15. The computer-program product of claim 11, wherein: the processorcomponent is incorporated into a node device of the first quantity ofnode devices; and the processor component is caused to retrieve, via anetwork, a portion of the data set from the data file as one of thefirst quantity of node devices at least partially in parallel with atleast one other node device of the first quantity of node devices. 16.The computer-program product of claim 15, wherein the processorcomponent is caused to perform the processing task with a portion of thedata set retrieved from the data file as the one of the first quantityof node devices at least partially in parallel with at least one othernode device of the first quantity of node devices.
 17. Thecomputer-program product of claim 11, wherein: the data file ismaintained by one or more storage devices; and the processor componentis caused to retrieve, from the one or more storage devices through anetwork, the map data and the metadata.
 18. The computer-program productof claim 17, wherein, to retrieve the map data from the data file, theprocessor component is caused to perform operations comprising:transmit, via the network, a first command to the one or more storagedevices to provide a map base of the data map from the data file;receive, via the network, a map base from the data file; analyze the mapbase to determine whether at least a portion of the map data is storedwithin one or more map extensions within the data file; and in responseto a determination that at least a portion of the map data is storedwithin one or more map extensions, perform operations comprising:transmit, via the network, a second command to the one or more storagedevices to provide at least one map extension of the one or more mapextensions; and receive, via the network, the at least one map extensionfrom the data file.
 19. The computer-program product of claim 11,wherein: the processor component is incorporated into a control devicecoupled to a grid of multiple node devices; and the processor componentis caused to perform operations comprising: recurringly receive, via anetwork, indications of availability to perform processing tasks fromeach node device of the multiple node devices; recurringly update astored indication of availability of each node device of the multiplenode devices; and analyze the stored indications of availability toidentify the first quantity of node devices.
 20. The computer-programproduct of claim 19, wherein the processor component is caused toperform operations comprising provide an indication of the processingtask to the first quantity of node devices to enable more than one nodedevice of the first quantity of node devices to each perform theprocessing task with a portion of the data set at least partially inparallel.
 21. A computer-implemented method comprising: analyzing, by aprocessor component, metadata indicative of an organization of datawithin a data set or map data indicative of an organization of multipledata blocks of the data set within a data file to determine whether thedata set comprises partitioned data; determining whether the analyzedmetadata indicates whether the data set comprises partitioned data,wherein when the data set comprises partitioned data the data set isorganized into multiple partitions and each whole partition isdistributable to a single node device to be processed; and in responseto a determination that data set does not comprise partitioned data,wherein the map data comprises multiple map entries in which each mapentry corresponds to one or more data blocks of the multiple datablocks, performing operations comprising: for each map entry of the mapdata, retrieving, from the map entry, a data block size and a data blockquantity, wherein the data block quantity indicates a quantity ofadjacent data blocks of the multiple data blocks within the data filethat correspond to the map entry; and for each data block thatcorresponds to the map entry: determining a location of thecorresponding data block within the data file; selecting one of a firstquantity of node devices that are currently available to perform aprocessing task; and providing a pointer to the selected one of thefirst quantity of node devices, wherein the pointer comprises: anindication of the location of the corresponding data block within thedata file; and the data block size.
 22. The computer-implemented methodof claim 21, wherein the selection of one of the first quantity nodedevices comprises a round robin selection of one of the first quantityof node devices.
 23. The computer-implemented method of claim 21,comprising: in response to a determination that the data set comprisespartitioned data, performing operations comprising: comparing, by theprocessor component, the first quantity of node devices to a secondquantity of node devices that were last involved in storage of the dataset within the data file; assigning, by the processor component, anumerical designation value to each node device of the first quantity ofnode devices; and in response to a match between the first and secondquantities of node devices, for each data block of the multiple datablocks, performing operations comprising: retrieving, from the map data,a hashed identifier for one data sub-block indicated by the map data tobe within the data block, wherein: the data sub-block comprises data ofthe data set that belongs to a partition of the multiple partitions; andthe hashed identifier is derived from a partition label of thepartition; retrieving, from the map data, a data sub-block size for eachof the data sub-blocks indicated by the map data to be within the datablock; determining a location of the data block within the data file;dividing the hashed identifier by the first quantity of node devices toobtain a modulo value; and transmitting a pointer to a node device ofthe first quantity of node devices that is assigned a designation valuethat matches the modulo value, wherein the pointer comprises: anindication of the location of the data block within the data file; and asum of data sub-block sizes of the data sub-blocks within the datablock.
 24. The computer-implemented method of claim 23, wherein inresponse to the determination that the data set comprises partitioneddata and in response to a lack of a match between the first and secondquantities of node devices, performing operations comprising: for eachdata sub-block within each data block of the multiple data blocks,performing operations comprising: retrieving, from the map data, thedata sub-block size and hashed identifier of the data sub-block;determining a location of the data sub-block within the data file;dividing the hashed identifier by the first quantity of node devices toobtain a modulo value; and providing a pointer to the node of the firstquantity of node devices that is assigned a designation value thatmatches the modulo value, wherein the pointer comprises: an indicationof the location of the data sub-block within the data file; and the datasub-block size of the data sub-block.
 25. The computer-implementedmethod of claim 21, wherein: the processor component is incorporatedinto a node device of the first quantity of node devices; and the methodcomprises retrieving, via a network, a portion of the data set from thedata file as one of the first quantity of node devices at leastpartially in parallel with at least one other node device of the firstquantity of node devices.
 26. The computer-implemented method of claim25, comprising performing, by the processor component, the processingtask with a portion of the data set retrieved from the data file as theone of the first quantity of node devices at least partially in parallelwith at least one other node device of the first quantity of nodedevices.
 27. The computer-implemented method of claim 21, wherein: thedata file is maintained by one or more storage devices; and the methodcomprises retrieving, from the one or more storage devices through anetwork, the map data and the metadata.
 28. The computer-implementedmethod of claim 27, wherein retrieving the map data from the data filecomprises: transmitting, via the network, a first command to the one ormore storage devices to provide a map base of the data map from the datafile; receiving, via the network, a map base from the data file;analyzing, by the processor component, the map base to determine whetherat least a portion of the map data is stored within one or more mapextensions within the data file; and in response to a determination thatat least a portion of the map data is stored within one or more mapextensions, performing operations comprising: transmitting, via thenetwork, a second command to the one or more storage devices to provideat least one map extension of the one or more map extensions; andreceiving, via the network, the at least one map extension from the datafile.
 29. The computer-implemented method of claim 21, wherein: theprocessor component is incorporated into a control device coupled to agrid of multiple node devices; and the method comprises: recurringlyreceiving, via a network, indications of availability to performprocessing tasks from each node device of the multiple node devices;recurringly updating, by the processor component, a stored indication ofavailability of each node device of the multiple node devices; andanalyzing, by the processor component, the stored indications ofavailability to identify the first quantity of node devices.
 30. Thecomputer-implemented method of claim 29, comprising providing anindication of the processing task to the first quantity of node devicesto enable more than one node device of the first quantity of nodedevices to each perform the processing task with a portion of the dataset at least partially in parallel.